Handbook of Research on Telecommunications Planning and Management for Business, 2-Volumes (Advances in E-Business Research Series)

Handbook of Research on Telecommunications Planning and Management for Business In Lee Western Illinois University, USA

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Handbook of research on telecommunications planning and management for business / In Lee, editor. p. cm. Includes bibliographical references and index. Summary: "This book provides original, in-depth, and innovative articles on telecommunications policy, management, and business applications"--Provided by publisher. ISBN 978-1-60566-194-0 (hbk.) -- ISBN 978-1-60566-195-7 (ebook) 1. Telecommunication. 2. Telecommunication policy. 3. Telecommunication systems--Management. I. Lee, In, 1958HE7631.H35 2009 384.068--dc22 2008041546 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. Handbook of Research on Telecommunications Planning and Management for Business is part of the IGI Global series named Advances in E-Business Research (AEBR) Series, ISBN: 1935-2700

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Advances in E-Business Research (AEBR) Series ISBN: 1935-2700 Editor-in-Chief: In Lee, Western Illinois University, USA

Handbook of Research on Telecommunications Planning and Management for Business Edited by: In Lee, Western Illinois University, USA ~ ISBN: 978-1-60566-194-0 ~ H/C ~ Copyright 2009 Information Science Reference ~ 1,194 pp ~ Our price: $ 495.00 Telecommunications planning and management has become increasingly important in this digital economy as significant implications for corporate strategies are constantly being developed. As these technologies continue to evolve and become key strategic assets in business organizations, researchers, higher education faculty, and practitioners are in great need of appropriate resources assisting their understanding of all aspects of telecommunications planning and management. Emergent Strategies for E-Business Processes, Services and Implications: Advancing Corporate Frameworks Edited by: In Lee, Western Illinois University, USA ISBN: 978-1-60566-154-4 ~ H/C ~ Copyright 2008 Information Science Reference ~ 424pp ~ Our Price: $195.00 Emergent Strategies for E-Business Processes, Services and Implications: Advancing Corporate Frameworks is an authoritative collection of original, in-depth, and innovative research articles on e-business concepts, models, processes, services, and applications. This book presents an integrated view of emerging issues and technologies addressed by renowned scholars, providing researchers and practitioners with the state-of the-art reference for future research and practices on a wide range of topics including e-CRM, e-business model, multi-channel management, e-health, m-commerce adoption, offshore outsourcing, and e-business innovation. E-Business Models, Services and Communications Edited by: In Lee, Western Illinois University, USA ISBN: 978-1-59904-831-4 ~ H/C ~ Copyright 2008 Information Science Reference ~ 464pp ~ Our Price: $180.00 E-Business Models, Services and Communications provides researchers and practitioners with valuable information on recent advances and developments in emerging e-business models and technologies. This book covers a variety of topics such as e-business models, telecommunication network utilization, online consumer behavior, electronic communication adoption and service provider strategies, and privacy policies and implementation issues.

The Advances in E-Business Research (AEBR) Book Series plans to serve as balanced interdisciplinary references for researchers and practitioners in this area. The AEBR Book Series intends to provide instructors, researchers, professionals, and students in higher education with a coherent collection of books that deals with the most current information about the concepts, issues, applications, technologies, and trends in the e-business area. AEBR publishes the highest quality academic books that foster our understanding of e-business and address the challenges and opportunities faced by the researchers and practitioners.

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Editorial Advisory Board Nick Antonopoulos, University of Surrey, UK Lisandro Zambenedetti Granville, Federal University of Rio Grande do Sul (UFRGS), Brazil Hyun-Soo Han, Hanyang University, South Korea Faouzi Kamoun, University of Dubai, UAE James Prieger, Pepperdine University, USA Jiayin Qi, Beijing University of Posts and Telecommunications, China Jadranka Skorin-Kapov, SUNY, Stony Brook, USA Iakovos S. Venieris, National Technical University of Athens, Greece Ran Wei, University of South Carolina, USA James G. Williams, University of Pittsburgh, USA

List of Reviewers Carl Adams, University of Portsmouth, UK Cajetan M. Akujuobi, Prairie View A&M University, USA Christos Anagnostopoulos, University of Athens, Greece Georgios Angelou, University of Macedonia, Greece Nick Antonopoulos, University of Surrey, UK Norm Archer, McMaster University, Canada Javier A. Barria, Imperial College, UK Daniel Birke, University of Nottingham, UK Mohamed Boucadair, France Telecom-Orange Labs, France Susan Chinburg, Rogers State University, USA Nicoletta Corrocher, Bocconi University, Italy Kevin Curran, University of Ulster, UK Rebecca De Coster, Brunel University, UK Pasquale De Meo, DIMET- University Mediterranea of Reggio Calabria, Italy Salah Eddine Elayoubi, France Telecom-Orange Labs, France Kalle Elfvengren, Lappeenranta University of Technology, Finland Károly Farkas, University of West Hungary, Hungary Kwo-Jean Farn, National Chiao-Tung University, Taiwan Roberto Fontana, University of Pavia, Italy Lauri Frank, University of Jyväskylä, Finland David Golightly, University of Nottingham, UK Ricardo Gonçalves, Universidade Católica Portuguesa (Porto), Portugal

Sotirios K. Goudos, Aristotle University of Thessaloniki, Greece Lisandro Granville, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Sami Habib, Kuwait University, Kuwait Hyun-Soo Han, Hanyang University, South Korea Sunil Hazari, University of West Georgia, USA Anders Henten, IMM, DTU, Denmark Dieter Hogrefe, University of Göttingen, Germany Stefan Hüsig, University of Regensburg, Germany Antonio Iera, University “Mediterranea” of Reggio Calabria, Italy Hamid Jahankhani, Middlesex University, UK Andrzej Jajszczyk, AGH University of Science and Technology, Poland Jacqueline Kam, University of Bristol, UK Faouzi Kamoun, University of Dubai, UAE Ben B. Kim, Seattle University, USA Moon-Koo Kim, Electronics and Telecommunications Research Institute, South Korea Moon-Soo Kim, Hankuk University of Foreign Studies, South Korea Eino Kivisaari, Helsinki University of Technology, Finland Heli Koski, The Research Institute of the Finnish Economy (ETLA), Finland Filippia Kotsilieri, University of Bath, UK Ying-Feng Kuo, National University of Kaohsiung, Taiwan Stan Kurkovsky, Central Connecticut State University, USA Riku Laanti, The University of Adelaide, USA Romain Laborde, IRIT - SIERA, Université Paul Sabatier, France Shu-Kuo Lin, National Chiao-Tung University, Taiwan Gitte Lindgaard, Carleton University, Canada Mirko L. Lobina, University of Cagliari, Italy Antti Lönnqvist, Tampere University of Technology, Finland Sunil Manvi, Basaveshwar Engineering College, India John Meisel, Southern Illinois University Edwardsville, USA Katina Michael, University of Wollongong, Australia John Mylonakis, Ministry of Economics and Finance, Greece John H. Nugent, University of Dallas, USA Jose J. Pazos-Arias, University of Vigo, Spain Krassie Petrova, Auckland University of Technology, New Zealand Lisa Pierce, Forrester Research, USA James Prieger, Pepperdine University, USA Kaisu Puumalainen, Lappeenranta University of Technology, Finland Alejandro Quintero, Ecole Polytechnique de Montreal, Canada Farzad Safaei, University of Wollongong, Australia Linda Salahaldin, Dauphine University, France Cristóbal Sánchez-Rodríguez, York University, Canada Reijo Savola, VTT Technical Research Centre of Finland, Finland George Scheets, Oklahoma State University, USA Carsten Schröer, University of Duisburg-Essen, Germany

Jadranka Skorin-Kapov, SUNY Stony Brook, USA Sanna Sundqvist, Lappeenranta University of Technology, Finland Ching-I Teng, Chang Gung University, Taiwan Nikolaos D. Tselikas, National Technical University of Athens, Greece Belén Usero Sánchez, Universidad Carlos III de Madrid, Spain Dimitris Varoutas, University of Athens, Greece Sofie Verbrugge, Ghent University/ IBBT, Belgium Xiaofei Wang, Indiana University, USA Michael R. Ward, The University of Texas at Arlington, USA Barney Warf, University of Kansas, USA Chong Chin Wei, Multimedia University, Malaysia Jason Whalley, University of Strathclyde, UK James G. Williams, University of Pittsburgh, USA Xiaotao Wu, Columbia University, USA Kaiqi Xiong, Texas A&M University Commerce, USA Kenneth C.C. Yang, The University of Texas at El Paso, USA Sherali Zeadally, University of the District of Columbia, USA Youlong Zhuang, Columbia College, USA

List of Contributors

Agorogianni, Angeliki Z. / Aristotle University of Thessaloniki, Greece.......................................... 615 Akujuobi, Cajetan M. / Prairie View A & M University, USA.......................................................... 760 Ampah, Nana K. / Prairie View A & M University, USA................................................................... 760 Ana García-Armada, University Carlos III de Madrid, Spain.......................................................... 788 Angelou, Georgios N. / University of Macedonia, Greece................................................................. 414 Antonopoulos, Nick / University of Surrey, UK ................................................................................ 882 Atzori, Luigi / Università di Cagliari, Italy........................................................................................ 689 Barco, Raquel / University of Málaga, Spain..................................................................................... 742 Baume, Georges / The University of Adelaide Business School, Australia........................................ 173 Bell, David / Pacific Union College, USA........................................................................................... 588 Bhajantri, L. B. / Basaveshwar Engineering College, India............................................................. 820 Boi, Fabrizio / Università di Cagliari, Italy....................................................................................... 689 Boucadair, Mohamed / France Telecom-Orange Labs, France........................................................ 672 Chinburg, Susan J. / Rogers State University, USA.......................................................................... 895 Chong, Chin Wei / Multimedia University, Malaysia........................................................................ 265 Chong, Siong Choy / Putra International College, Malaysia............................................................ 265 Corrocher, Nicoletta / Bocconi University, Italy and University of Tromso, Norway....................... 447 De Coster, Rebecca / Brunel University, UK...................................................................................... 433 Distaso, Walter / Imperial College London, UK ................................................................................... 1 Economides, Anastasios A. / University of Macedonia, Greece........................................................ 414 Elayoubi, Salah Eddine / Orange Labs, France................................................................................ 400 Escudero-Garzás, J. Joaquín / University Carlos III de Madrid, Spain........................................... 804 Farkas, Károly / University of West Hungary, Hungary.................................................................... 634 Feijóo, Claudio / Universidad Politécnica de Madrid, Spain.............................................................. 33 Fernández, Zulima / Universidad Carlos III de Madrid, Spain........................................................ 194 Fioreze, Tiago / Federal University of Rio Grande do Sul – Porto Alegre, Brazil............................. 724 Fontana, Roberto / University of Pavia, Italy and Bocconi University, Italy.................................... 447 García-Armada, Ana / University Carlos III de Madrid, Spain........................................................ 804 Gershon, Richard A. / Western Michigan University, USA............................................................... 461 Golightly, David / University of Nottingham, UK.............................................................................. 653 Gómez-Barroso, José Luis / Universidad Nacional de Educación a Distancia (UNED), Spain........ 33 Gonçalves, Ricardo / Universidade Católica Portuguesa (Porto), Portugal...................................... 48 Goudos, Sotirios K. / Aristotle University of Thessaloniki, Greece................................................... 615 Granville, Lisandro Zambenedetti / Federal University of Rio Grande do Sul – Porto Alegre, Brazil............................................................................................................................................... 724

Han, Hyun-Soo / Hanyang University, South Korea.................................................................. 222, 234 Hartleb, Franz / T-Systems, Germany................................................................................................ 852 Haßlinger, Gerhard / T-Systems, Germany................................................................................ 852, 867 Hazari, Sunil / University of West Georgia, USA............................................................................... 588 Heil, Daniel / Pepperdine University, USA........................................................................................... 15 Hill, Sally Rao / University of Adelaide, Australia............................................................................... 88 Hopper, Trevor / University of Manchester, UK................................................................................ 281 Horváth, Zoltán / Budapest University of Technology & Economics, Hungary................................ 634 Hüsig, Stefan / University of Regensburg, Germany.......................................................................... 108 J. Joaquín Escudero-Garzás / University Carlos III de Madrid, Spain............................................ 788 Johnston, Wesley J. / Georgia State University, USA........................................................................ 248 Kakkasageri, M. S. / Basaveshwar Engineering College, India........................................................ 599 Kamoun, Faouzi / University of Dubai, UAE.................................................................................... 526 Kanellopoulos, Dimitris / University of Patras, Greece.................................................................... 775 Kapitsaki, Georgia M. / National Technical University of Athens, Greece...................................... 703 Kargas, Antonios D. / University of Athens, Athens, Greece..................................................... 295, 310 Kempken, Sebastian / University of Duisburg-Essen, Germany....................................................... 852 Kim, Moon-Koo / Electronics and Telecommunications Research Institute, South Korea................ 351 Kim, Moon-Soo / Hankuk University of Foreign Studies, Korea....................................................... 141 Kollmann, Tobias / University of Duisburg-Essen, Campus Essen, Germany.................................. 557 Kurkovsky, Stan / Central Connecticut State University, USA......................................................... 474 Laanti, Riku / The University of Adelaide Business School, Australia.............................................. 173 Lázaro, Pedro / University of Málaga, Spain..................................................................................... 742 Lee, Heesang / Sungkyunkwan University, South Korea............................................................ 222, 234 Levis, Pierre / France Telecom-Orange Labs, France....................................................................... 672 Li, Chen / Beijing University of Posts and Telecommunications, China............................................ 379 Li, Yuanquan / Beijing University of Posts and Telecommunications, China.................................... 379 Lobina, Mirko Luca / Università di Cagliari, Italy........................................................................... 689 Low, Brian / University of Western Sydney, Australia........................................................................ 248 Lupi, Paolo / AGCOM, Italy ................................................................................................................. 1 Major, Maria / ISCTE – Business School, Portugal.......................................................................... 281 Makris, Dimitrios G. / University of Peloponnese, Greece............................................................... 703 Manenti, Fabio / Università di Padova, Italy......................................................................................... 1 Manvi, S. S. / REVA Institute of technology and Management, India........................................ 599, 820 McDonough, Carol C. / University of Massachusetts Lowell, USA.................................................... 65 McDougall, Fred / The University of Adelaide, Australia.................................................................. 173 McKinion, James M. / USDA-ARS, USA........................................................................................... 836 Meisel, John B. / Southern Illinois University Edwardsville, USA..................................................... 125 Mochón, Asunción / Universidad Nacional de Educación a Distancia (UNED), Spain..................... 33 Morand, Pierrick / France Telecom-Orange Labs, France............................................................... 672 Morlot, Frédéric / Orange Labs, France........................................................................................... 400 Nascimento, Álvaro / Universidade Católica Portuguesa (Porto), Portugal...................................... 48 Neisse, Ricardo / Federal University of Rio Grande do Sul – Porto Alegre, Brazil.......................... 724 Olla, Phillip /, Madonna University, USA........................................................................................... 517 Park, Jong-Hyun / Electronics and Telecommunications Research Institute, South Korea.............. 351 Park, Myeong-Cheol / Information and Communications University, South Korea......................... 351

Parlanti, Claudia / Bocconi University, Italy..................................................................................... 447 Perros, Harry / North Carolina State University, USA...................................................................... 927 Pierre, Samuel / École Polytechnique de Montréal, Canada............................................................. 515 Prieger, James E. / Pepperdine University, USA.................................................................................. 15 Qi, Jiayin / Beijing University of Posts and Telecommunications, China.................................. 364, 379 Ramadan, Salah / Azhar University, Egypt........................................................................................ 909 Salter, James / University of Surrey, UK............................................................................................ 882 Sánchez, Belén Usero / Universidad Carlos III de Madrid, Spain.................................................... 194 Sawng, Yeong -Wha / Electronic and Telecommunications Research Institute, South Korea.............................................................................................................................. 222, 234 Scheets, George / Oklahoma State University, USA........................................................................... 895 Schröer, Carsten / University of Duisburg-Essen, Campus Essen, Germany.................................... 557 Shin, Dong Hee / Penn State University, Berks Campus, USA........................................................... 158 Si, Yajing / Beijing Wuzi University, China......................................................................................... 364 Skorin-Kapov, Darko / Adelphi University, USA.............................................................................. 941 Skorin-Kapov, Jadranka / Stony Brook University, USA.................................................................. 941 St-Hilaire, Marc / Carleton University, Canada................................................................................ 515 Stöckmann, Christoph / University of Duisburg-Essen, Campus Essen, Germany.......................... 557 Sullivan, Timothy S. / Southern Illinois University Edwardsville, USA............................................ 125 Szabó, Csaba A. / Budapest University of Technology & Economics, Hungary................................ 634 Tan, Jing / Beijing University of Posts and Telecommunications, China................................... 364, 379 Tarnay, Katalin / University of Pannonia, Hungary.................................................................. 488, 502 Troshani, Indrit / University of Adelaide, Australia............................................................................ 88 Tselikas, Nikolaos D. / University of Peloponnese, Greece............................................................... 703 Varoutas, Dimitris / University of Athens, Athens, Greece........................................................ 295, 310 Venieris, Iakovos S. / National Technical University of Athens, Greece............................................ 703 Verkasalo, Hannu / Helsinki University of Technology, Finland....................................................... 324 Vianna, Ricardo Lemos / Federal University of Rio Grande do Sul – Porto Alegre, Brazil............ 724 Warf, Barney / University of Kansas, USA........................................................................................ 208 Wei, Ran / University of South Carolina, USA................................................................................... 542 Xiong, Kaiqi / Texas A&M University, USA....................................................................................... 927 Zaharis, Zaharias D. / Aristotle University of Thessaloniki, Greece................................................. 615 Zaki, Mohamed / Azhar University, Egypt......................................................................................... 909 Zhang, Yangming / Beijing University of Posts and Telecommunications, China............................. 364 Zhang, Yingying / Beijing University of Posts and Telecommunications, China.............................. 379 Zhao, Zizhong / Communication University of China, China............................................................ 542

Table of Contents

Foreword . .....................................................................................................................................xxxviii Preface . ............................................................................................................................................... xlv Acknowledgment . ...............................................................................................................................liii Volume I Section I Telecommunications Policy Chapter I Static and Dynamic Efficiency in the European Telecommunications Market: The Role of Regulation on the Incentives to Invest and the Ladder of Investment ............................... 1 Walter Distaso, Imperial College London, UK Paolo Lupi, AGCOM, Italy Fabio M. Manenti, Università di Padova, Italy Chapter II Is Regulation a Roadblock on the Information Highway? ................................................................... 15 James E. Prieger, Pepperdine University, USA Daniel Heil, Pepperdine University, USA Chapter III Reforms in Spectrum Management Policy ........................................................................................... 33 Claudio Feijóo, Universidad Politécnica de Madrid, Spain José Luis Gómez-Barroso, Universidad Nacional de Educación a Distancia (UNED), Spain Asunción Mochón, Universidad Nacional de Educación a Distancia (UNED), Spain Chapter IV Next Generation Access Networks and their Regulatory Implications ................................................ 48 Ricardo Gonçalves, Universidade Católica Portuguesa (Porto), Portugal Álvaro Nascimento, Universidade Católica Portuguesa (Porto), Portugal

Chapter V The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry................................................................................................................................ 65 Carol C. McDonough, University of Massachusetts Lowell, USA Chapter VI Shaping Regulation in the Australian Mobile Industry ........................................................................ 88 Indrit Troshani, University of Adelaide, Australia Sally Rao Hill, University of Adelaide, Australia

Section II Telecommunications Industry Chapter VII Analyzing the Disruptive Potential in the Telecommunications Industry........................................... 108 Stefan Hüsig, University of Regensburg, Germany Chapter VIII Convergence of the Internet and Telecommunications........................................................................ 125 John B. Meisel, Southern Illinois University Edwardsville, USA Timothy S. Sullivan, Southern Illinois University Edwardsville, USA Chapter IX International Internet Interconnection Service in Asia-Pacific Region .............................................. 141 Moon-Soo Kim, Hankuk University of Foreign Studies, Korea Chapter X A Techno-Economic Analysis of Mobile Virtual Network Operators................................................. 158 Dong Hee Shin, Penn State University, Berks Campus, USA Chapter XI Evolving Value Networks and Internationalisation of National Telecommunication Companies from Small and Open Economies .................................................................................... 173 Riku Laanti, The University of Adelaide Business School, Australia Fred McDougall, The University of Adelaide, Australia Georges Baume, The University of Adelaide Business School, Australia Chapter XII The Effect of Non-Market Strategies in the Mobile Industry . ........................................................... 194 Zulima Fernández, Universidad Carlos III de Madrid, Spain Belén Usero Sánchez, Universidad Carlos III de Madrid, Spain

Chapter XIII Spatiality and Political Economy of the Global Fiber Optics Industry............................................... 208 Barney Warf, University of Kansas, USA Chapter XIV Digital Convergence and Home Network Services in Korea: Part 1 - Recent Progress and Policy Implications.......................................................................................................................................... 222 Hyun-Soo Han, Hanyang University, South Korea Heesang Lee, Sungkyunkwan University, South Korea Yeong -Wha Sawng, Electronic and Telecommunications Research Institute, South Korea Chapter XV Digital Convergence and Home Network Services in Korea: Part 2 – Business Models and Strategic Alliances............................................................................................................................... 234 Hyun-Soo Han, Hanyang University, South Korea Heesang Lee, Sungkyunkwan University, South Korea Yeong -Wha Sawng, Electronic and Telecommunications Research Institute, South Korea

Section III Telecommunications Business Management Chapter XVI Mixing and Matching Organizational Network Legitimacy Practices to China’s Telecommunication Market................................................................................................................. 248 Brian Low, University of Western Sydney, Australia Wesley J. Johnston, Georgia State University, USA Chapter XVII Preliminary Knowledge Management Implementation in the Telco Industry..................................... 265 Chin Wei Chong, Multimedia University, Malaysia Siong Choy Chong, Putra International College, Malaysia Chapter XVIII Activity-Based Costing in the Portuguese Telecommunications Industry........................................... 281 Maria Major, ISCTE – Business School, Portugal Trevor Hopper, University of Manchester, UK Chapter XIX The Role of Organizational Culture to the Management of Telecommunication Companies: I. Background and Motivation............................................................................................................. 295 Antonios D. Kargas, University of Athens, Athens, Greece Dimitris Varoutas, University of Athens, Athens, Greece

Chapter XX The Role of Organizational Culture to the Management of Telecommunication Companies: II. Applications and Case Studies........................................................................................................ 310 Antonios D. Kargas, University of Athens, Athens, Greece Dimitris Varoutas, University of Athens, Athens, Greece Chapter XXI Dynamics of Mobile Service Adoption................................................................................................ 324 Hannu Verkasalo, Helsinki University of Technology, Finland Chapter XXII When Customer Satisfaction Isn’t Good Enough: The Role of Switching Incentives and Barriers Affecting Customer Behavior in Korean Mobile Communications Services........................ 351 Moon-Koo Kim, Electronics and Telecommunications Research Institute, Korea Myeong-Cheol Park, Information and Communications University, Korea Jong-Hyun Park, Electronics and Telecommunications Research Institute, Korea Chapter XXIII Telecommunication Customer Demand Management . ...................................................................... 364 Jiayin Qi, Beijing University of Posts and Telecommunications, China Yajing Si, Beijing Wuzi University, China Jing Tan, Beijing University of Posts and Telecommunications, China Yangming Zhang, Beijing University of Posts and Telecommunications, China Chapter XXIV Telecommunication Customer Detainment Management.................................................................... 379 Jiayin Qi, Beijing University of Posts and Telecommunications, China Yuanquan Li, Beijing University of Posts and Telecommunications, China Chen Li, Beijing University of Posts and Telecommunications, China Yingying Zhang, Beijing University of Posts and Telecommunications, China Jing Tan, Beijing University of Posts and Telecommunications, China Chapter XXV How to Plan for an Upgrading Investment in a Data Network?.......................................................... 400 Frédéric Morlot, Orange Labs, France Salah Eddine Elayoubi, Orange Labs, France Chapter XXVI Telecommunication Investments Analysis: A Multi-Criteria Model................................................... 414 Georgios N. Angelou, University of Macedonia, Greece Anastasios A. Economides, University of Macedonia, Greece Chapter XXVII A Business Planning Framework for WiMAX Applications............................................................... 433 Rebecca De Coster, Brunel University, UK

Chapter XXVIII Adoption of VoIP Applications in Public and Private Organizations.................................................. 447 Nicoletta Corrocher, Bocconi University, Italy and University of Tromso, Norway Roberto Fontana, University of Pavia, Italy and Bocconi University, Italy Claudia Parlanti, Bocconi University, Italy Chapter XXIX Intelligent Networking and Business Process Innovation: A Case Study Analysis of Home Box Office and Dell Computers................................................................................................ 461 Richard A. Gershon, Western Michigan University, USA Chapter XXX Can M-Commerce Benefit from Pervasive Computing?..................................................................... 474 Stan Kurkovsky, Central Connecticut State University, USA

Section IV Telecommunications Technology Management Chapter XXXI Basics of Telecommunication Management........................................................................................ 488 Katalin Tarnay, University of Pannonia, Hungary Chapter XXXII Telecommunication Management Protocols........................................................................................ 502 Katalin Tarnay, University of Pannonia, Hungary Chapter XXXIII Cellular Network Planning: Evolution from 2G to 4G........................................................................ 515 Marc St-Hilaire, Carleton University, Canada Samuel Pierre, École Polytechnique de Montréal, Canada

Volume II Chapter XXXIV IP Address Management: Challenges, Solutions and Future Perspectives.......................................... 526 Faouzi Kamoun, University of Dubai, UAE Chapter XXXV Digital Cable TV Networks: Converging Technologies, Value-Added Services and Business Strategies........................................................................................................................ 542 Ran Wei, University of South Carolina, USA Zizhong Zhao, Communication University of China, China

Chapter XXXVI Diffusion and Oscillation of Telecommunications Services: The Case of Web 2.0 Platforms............ 557 Tobias Kollmann, University of Duisburg-Essen, Campus Essen, Germany Christoph Stöckmann, University of Duisburg-Essen, Campus Essen, Germany Carsten Schröer, University of Duisburg-Essen, Campus Essen, Germany Chapter XXXVII The Diffusion of WiMax Technology: Hurdles and Opportunities..................................................... 571 Phillip Olla, Madonna University, USA Chapter XXXVIII VoIP Quality and Security Issues for Consumers and Small Businesses............................................. 588 David Bell, Pacific Union College, USA Sunil Hazari, University of West Georgia, USA Chapter XXXIX Emerging Security Issues in VANETS for E-Business........................................................................ 599 S. S. Manvi, REVA Institute of Technology and Management, India M. S. Kakkasageri, Basaveshwar Engineering College, India Chapter XL Telecommunications Network Planning and Operations Management in an Academic Environment: The Case Study of the Aristotle University of Thessaloniki......................................... 615 Sotirios K. Goudos, Aristotle University of Thessaloniki, Greece Angeliki Z. Agorogianni, Aristotle University of Thessaloniki, Greece Zaharias D. Zaharis, Aristotle University of Thessaloniki, Greece Chapter XLI Planning of Wireless Community Networks........................................................................................ 634 Károly Farkas, University of West Hungary, Hungary Csaba A. Szabó, Budapest University of Technology & Economics, Hungary Zoltán Horváth, Budapest University of Technology & Economics, Hungary Chapter XLII Human Factors for Business Mobile Systems..................................................................................... 653 David Golightly, University of Nottingham, UK

Section V Telecommunications Technology and Applications Chapter XLIII Towards QoS-Inferred Internet............................................................................................................ 672 Mohamed Boucadair, France Telecom-Orange Labs, France Pierre Levis, France Telecom-Orange Labs, France Pierrick Morand, France Telecom-Orange Labs, France Chapter XLIV The Playout Control Management: An Issue for the IP Telephony Service Providers........................ 689 Mirko Luca Lobina, Università di Cagliari, Italy Luigi Atzori, Università di Cagliari, Italy Fabrizio Boi, Università di Cagliari, Italy Chapter XLV Open APIs and Protocols for Services and Applications in Telecoms................................................. 703 Nikolaos D. Tselikas, University of Peloponnese, Greece Georgia M. Kapitsaki, National Technical University of Athens, Greece Dimitrios G. Makris, University of Peloponnese, Greece Iakovos S. Venieris, National Technical University of Athens, Greece Chapter XLVI On the Management Performance of Networked Environments Using Web Services Technologies.......................................................................................................................... 724 Lisandro Zambenedetti Granville, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Ricardo Neisse, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Ricardo Lemos Vianna, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Tiago Fioreze, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Chapter XLVII Automated Fault Management in Wireless Networks ........................................................................ 742 Raquel Barco, University of Málaga, Spain Pedro Lázaro, University of Málaga, Spain Chapter XLVIII Modeling Intrusion Detection with Self Similar Traffic in Enterprise Networks . ............................. 760 Cajetan M. Akujuobi, Prairie View A & M University, USA Nana K. Ampah, Prairie View A & M University, USA

Chapter XLIX High-Speed Multimedia Networks: Critical Issues and Trends........................................................... 775 Dimitris Kanellopoulos, University of Patras, Greece Chapter L Emerging Telecommunications Technologies: Cognitive Radio......................................................... 788 J. Joaquín Escudero-Garzás, University Carlos III de Madrid, Spain Ana García-Armada, University Carlos III de Madrid, Spain Chapter LI Game Theory for PHY Layer and MAC Sublayer in Wireless Telecommunications......................... 804 J. Joaquín Escudero-Garzás, University Carlos III de Madrid, Spain Ana García-Armada, University Carlos III de Madrid, Spain Chapter LII Agent Based Product Negotiation Models in Mobile Commerce....................................................... 820 S. S. Manvi, REVA Institute of Technology and Management, India L. B. Bhajantri, Basaveshwar Engineering College, India Chapter LIII Role of Telecommunications in Precision Agriculture........................................................................ 836 James M. McKinion, USDA-ARS, USA

Section VI Telecommunications Network Design Chapter LIV Network Planning and Dimensioning for Broadband Access to the Internet Regarding Quality of Service Demands................................................................................................................ 852 Franz Hartleb, T-Systems, Germany Gerhard Haßlinger, T-Systems, Germany Sebastian Kempken, University of Duisburg-Essen, Germany Chapter LV Overlay Networks: New Techniques for Global Service and Network Provisioning.......................... 867 Gerhard Haßlinger, T-Systems, Germany Chapter LVI Optimising P2P Networks by Adaptive Overlay Construction............................................................ 882 James Salter, University of Surrey, UK Nick Antonopoulos, University of Surrey, UK

Chapter LVII Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier....................... 895 Susan J. Chinburg, Rogers State University, USA George Scheets, Oklahoma State University, USA Chapter LVIII Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS................. 909 Mohamed Zaki, Azhar University, Egypt Salah Ramadan, Azhar University, Egypt Chapter LIX Secure Resource Optimization in Distributed Service Computing...................................................... 927 Kaiqi Xiong, Texas A&M University, USA Harry Perros, North Carolina State University, USA Chapter LX Trends, Optimization and Management of Optical Networks............................................................. 941 Jadranka Skorin-Kapov, Stony Brook University, USA Darko Skorin-Kapov, Adelphi University, USA

Compilation of References................................................................................................................ 957

Detailed Table of Contents

Foreword . .....................................................................................................................................xxxviii Preface . ............................................................................................................................................... xlv Acknowledgment . ...............................................................................................................................liii

Volume I Section I Telecommunications Policy Chapter I Static and Dynamic Efficiency in the European Telecommunications Market: The Role of Regulation on the Incentives to Invest and the Ladder of Investment ............................... 1 Walter Distaso, Imperial College London, UK Paolo Lupi, AGCOM, Italy Fabio M. Manenti, Università di Padova, Italy This chapter provides evidence of the effectiveness of European national regulatory authorities in applying the basic principles of the ladder of investment. The analysis discusses and compares the regulatory approach adopted in 12 European countries from January 2005 to July 2007. This chapter concludes that the policies adopted by national regulatory authorities are broadly consistent with the ladder of investment theory. Chapter II Is Regulation a Roadblock on the Information Highway? ................................................................... 15 James E. Prieger, Pepperdine University, USA Daniel Heil, Pepperdine University, USA Regulatory policy in telecommunications must balance short-term efficiency (low prices) against the firms’ incentives to innovate, which have longer reaching impacts on economic welfare. This chapter covers the theoretical and empirical impacts regulation has on innovation. There is consistent empirical evidence that regulation dampens firms’ incentive to innovate in the telecommunications industry

in general and the market for broadband Internet access in particular. Both product and process (cost reducing) innovation is discussed. The chapter forms a compendium of available research on the intersection of telecommunications regulation and innovation. Chapter III Reforms in Spectrum Management Policy ........................................................................................... 33 Claudio Feijóo, Universidad Politécnica de Madrid, Spain José Luis Gómez-Barroso, Universidad Nacional de Educación a Distancia (UNED), Spain Asunción Mochón, Universidad Nacional de Educación a Distancia (UNED), Spain Wireless/mobile technologies are absolutely necessary for any agent who wants to participate in the new information and communication technologies markets playfield. The mean for the deployment of the wireless/mobile technologies is the radio spectrum. A rational assignment and an efficient use of radio spectrum become sine qua non condition for the sector development. This chapter presents the reforms in the radioelectric spectrum management mechanisms that are currently being drafted (or that are even being applied) as well as to assess their advisability and timeliness. In particular, the chapter assesses the three deepest changes that are being considered: authorization of the secondary market, usage of auctions for primary allocation, and full liberalisation of spectrum usage. Chapter IV Next Generation Access Networks and their Regulatory Implications ................................................ 48 Ricardo Gonçalves, Universidade Católica Portuguesa (Porto), Portugal Álvaro Nascimento, Universidade Católica Portuguesa (Porto), Portugal The deployment of Next Generation Access networks (NGAs) is likely to have a significant impact on the telecommunications’ value chain and, consequently, on the necessary regulatory remedies. In particular, unlike existing telephone networks, NGAs present regulators with a dilemma, in so far as the possibility of regulatory intervention after network deployment (negatively) affects investment incentives for such a deployment. This chapter reviews the current discussion surrounding NGAs and discusses some of the main regulatory challenges it presents. Chapter V The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry................................................................................................................................ 65 Carol C. McDonough, University of Massachusetts Lowell, USA The United States’ wireless telephone industry has evolved from a minor segment of the communications industry to a major provider of voice, and increasingly data and video communication. The industry uses radio waves to transmit signals, and radio wave spectrum is regulated by the federal government. Moreover, local transmission requires unobstructed antennae, which in rural and suburban areas has led to the construction of wireless towers. States and municipalities have sought to regulate the construction of such towers, citing issues of aesthetics and health. The development of the wireless industry has been constrained by such government regulation. This chapter discusses the impact of government on the market structure of the wireless industry.

Chapter VI Shaping Regulation in the Australian Mobile Industry ........................................................................ 88 Indrit Troshani, University of Adelaide, Australia Sally Rao Hill, University of Adelaide, Australia The adoption and diffusion of mobile services has achieved a spectacular growth in many countries around the world. This chapter employs qualitative evidence to investigate how regulation and legislation can affect mobile services in the Australian mobile telecommunications industry and draws from it to propose an innovative regulatory framework based on a co-regulatory approach.

Section II Telecommunications Industry Chapter VII Analyzing the Disruptive Potential in the Telecommunications Industry........................................... 108 Stefan Hüsig, University of Regensburg, Germany This chapter covers an important issue in the area of telecommunications planning and technology management: The ex ante analysis of potential disruptive technologies. Due to the convergence of IT and telecommunications, an ever-growing onslaught of emerging technologies and new entrants with new business models are starting to eat up the incumbent’s revenues, profits, and market shares. In this chapter, the theory of disruptive technology, the concept of disruptive potential and a method for applying this concept in a telecommunications planning and technology management context is presented. Some examples of potential disruptive technologies in telecommunication which were analyzed ex ante are introduced with specific emphasis placed on the WLAN-technology. Chapter VIII Convergence of the Internet and Telecommunications........................................................................ 125 John B. Meisel, Southern Illinois University Edwardsville, USA Timothy S. Sullivan, Southern Illinois University Edwardsville, USA Convergence is fundamentally changing the nature of what it means to be a telecommunications company and promises to alter the market structure of many voice, data, and video markets. This chapter provides a framework to explain the convergence of communications networks and identifies and analyzes key issues that confront public policymakers. One key competition issue, termed network neutrality, addresses the concern that the evolving broadband network architecture will enable network providers to favor the provider’s services or affiliated services at the expense of independent rivals. Chapter IX International Internet Interconnection Service in Asia-Pacific Region .............................................. 141 Moon-Soo Kim, Hankuk University of Foreign Studies, Korea

Since 1986, the Internet has developed into a global network enabling users worldwide to connect to each other to exchange information and data. This chapter focuses on current interconnection settlement arrangement models that disfavor ISPs and end-users in the Asia-Pacific region. After reviewing the Internet market and digital divide in the region, the chapter summarizes the main current IIS issues between the Asia-Pacific and Western regions into three categories of concern: inequity, anticompetitive practices and the threat of the “balkanization” of the Internet. Practical recommendations to resolve these issues and improve the Asia-Pacific IIS market are discussed from regional and international perspectives. Chapter X A Techno-Economic Analysis of Mobile Virtual Network Operators................................................. 158 Dong Hee Shin, Penn State University, Berks Campus, USA This chapter examines cross-national data in order to identify possible factors related to the observable patterns of Mobile Virtual Network Operator (MVNO) penetration. The study conducts an economic assessment of market structure and environment for different countries’ MVNO penetration. The data on market structure is analyzed by means of cluster/factor analysis techniques in order to group countries according to their market environments. Then, regression equation analysis is used to investigate the relations of MVNO penetration and independent variables. The results show that MVNO penetration significantly relates to market structure and performance. These results also imply an appropriate policy to promote MVNO diffusion. Chapter XI Evolving Value Networks and Internationalisation of National Telecommunication Companies from Small and Open Economies .................................................................................... 173 Riku Laanti, The University of Adelaide Business School, Australia Fred McDougall, The University of Adelaide, Australia Georges Baume, The University of Adelaide Business School, Australia This chapter focuses on the internationalization processes of national telecommunications companies (telcos) from small and open economies (SMOPECs) who have moved from a domestic monopoly to an actor within the global industry. This chapter aims to increase our understanding of how these companies have internationalized, what factors have been the most influential in this process, and how the position of these companies has changed in the evolving value network of the industry. Case examples are used to illustrate the internationalization processes of telcos from SMOPECs within the context of the whole industry value network. Chapter XII The Effect of Non-Market Strategies in the Mobile Industry . ........................................................... 194 Zulima Fernández, Universidad Carlos III de Madrid, Spain Belén Usero Sánchez, Universidad Carlos III de Madrid, Spain This chapter analyzes the role of non-market actions (NMAs) in the competitive position of firms in the European mobile telecommunications industry. First, the bases and uses of NMAs are reviewed and classified. Second, the use of legal actions as NMAs to erode the competitive position of first-mover

firms is examined. Third, the findings of an empirical study confirming the effectiveness of legal actions as competition tools in the European mobile telecommunications industry are analyzed. Chapter XIII Spatiality and Political Economy of the Global Fiber Optics Industry............................................... 208 Barney Warf, University of Kansas, USA Fiber optics forms the pivotal telecommunications technology of the contemporary global economy, offering greater speed and security than other modes. This chapter reviews the historical development of this communications technique. It then views its rapid growth within the context of contemporary globalization. Fiber’s role in contemporary urban restructuring is noted. The chapter then turns to the spatial distribution of the world’s fiber lines, noting major transatlantic and transpacific markets and newer systems. Chapter XIV Digital Convergence and Home Network Services in Korea: Part 1 - Recent Progress and Policy Implications.............................................................................................................................. 222 Hyun-Soo Han, Hanyang University, South Korea Heesang Lee, Sungkyunkwan University, South Korea Yeong -Wha Sawng, Electronic and Telecommunications Research Institute, South Korea This chapter categorizes three classes of typical services and five industrial participants with regard to Korea’s home network industry. The chapter examines the government plans on home network services in the early stage of evolution, consumer value expectations and current home network service levels. Then, the chapter investigates business interests of the industrial participants comprising convergent home network services, and explores the causes of conflicts among them. The chapter offered policy suggestions from digital convergence perspective to help removing the obstacles that hinder business cooperation among industrial participants of the home network industry. Chapter XV Digital Convergence and Home Network Services in Korea: Part 2 – Business Models and Strategic Alliances............................................................................................................................... 234 Hyun-Soo Han, Hanyang University, South Korea Heesang Lee, Sungkyunkwan University, South Korea Yeong -Wha Sawng, Electronic and Telecommunications Research Institute, South Korea This chapter discusses managerial implications and strategic alliance opportunities of the home network service providers in Korea. Based on in-depth analysis of recent industrial status of home network services in Korea, the chapter first analyzes business models of each interested parties participating converging services of home network industry. Next, in order to complement the weakness of participant’s business models, strategic business alliance opportunities and managerial implications are drawn upon resourcebased view (RBV) theories. Subsequently, strategic propositions for the success of the home network are suggested at the firm level, with respect to three main converging home network services.

Section III Telecommunications Business Management Chapter XVI Mixing and Matching Organizational Network Legitimacy Practices to China’s Telecommunication Market......................................................... 248 Brian Low, University of Western Sydney, Australia Wesley J. Johnston, Georgia State University, USA Despite massive investment, few foreign firms doing business in China’s telecommunication sector can claim success. Such failures can be explained by their inability to acquire organizational legitimacy. Drawing on institutional theory, this chapter presents a case research based framework to describe an iterative and incremental process to help firms manage their network legitimacy. Using this framework, the chapter examines the complementary assets and legitimacy orientations of these firms with network stakeholders, and the resulting inter-partner initiatives and alliances. Chapter XVII Preliminary Knowledge Management Implementation in the Telco Industry..................................... 265 Chin Wei Chong, Multimedia University, Malaysia Siong Choy Chong, Putra International College, Malaysia This chapter aims to create a unified model capturing and generalizing the different arrays of preliminary knowledge management (KM) implementation success factors in the telecommunication industry based on the studies conducted on this sector in Malaysia. The literature and empirical evidence suggest that to become the leading global market players in the new knowledge society, telecommunication organizations are required to have the integration of an effective KM process which consists of construction, embodiment, and deployment. These processes must be supported by five preliminary success factors and effective KM strategies. Chapter XVIII Activity-Based Costing in the Portuguese Telecommunications Industry........................................... 281 Maria Major, ISCTE – Business School, Portugal Trevor Hopper, University of Manchester, UK This chapter examines an implementation of an Activity-based Costing (ABC) system in a specific Portuguese telecommunications firm which provided international telecommunications services. The chapter explores how ABC was adopted and used to support decision-making and pricing strategies. It is argued that they changed its management accounting system due to efficiency and institutional pressures from its constituencies, namely the Portuguese telecommunications regulator, its managers, and its competitors following the liberalization of the Portuguese and European Union telecommunications market. Divided reactions of the managers give support to both advocates of ABC and its critics who claim it is beset with problems of economic measurement, behavioral issues during implementation and operation, and questionable cost-benefit returns.

Chapter XIX The Role of Organizational Culture to the Management of Telecommunication Companies: I. Background and Motivation............................................................................................................. 295 Antonios D. Kargas, University of Athens, Athens, Greece Dimitris Varoutas, University of Athens, Athens, Greece This chapter explains what organizational culture is and analyzes its importance for the management of any company. Organizational culture must not be ignored during the decision-making process and managers must understand the existing culture of their organization in order to achieve their targets and to meet their goals. This chapter presents the theoretical link between organizational culture and a variety of variables, which affect organizational performance and efficiency, directly and indirectly. Such variables are knowledge management, organizational climate, leadership, quality, innovation and entrepreneurship, human resource management, and employee behavior. Chapter XX The Role of Organizational Culture to the Management of Telecommunication Companies: II. Applications and Case Studies........................................................................................................ 310 Antonios D. Kargas, University of Athens, Athens, Greece Dimitris Varoutas, University of Athens, Athens, Greece This chapter analyzes the importance of organizational culture through a set of strategies and enterprising practices in order to emphasize the culture’s necessity for the effective management of any organization and especially for the management of telecommunication companies. The way culture affects the success and failure of a series of enterprising practices, such as mergers, acquisitions, strategic alliances and joint ventures is presented. All these create a rather interesting framework in which organizational managers should cultivate and implement the appropriate organizational culture in order to keep their organization competitive and well managed. Finally, case studies from the telecommunications industry will be presented, a field where culture plays a dominant role in either changing procedure or in developing new enterprising practices. Chapter XXI Dynamics of Mobile Service Adoption................................................................................................ 324 Hannu Verkasalo, Helsinki University of Technology, Finland This chapter discusses the adoption of mobile services. Not all mobile services experience equal interest among end-users. Furthermore, not all interest towards the service leads to actual use of the service. This chapter studies the dynamics of mobile service adoption in a cross-service setting both qualitatively and quantitatively. The study explores what drives the intention and actual use of some of the emerging mobile services, thus contributing to both industry and academic readers.

Chapter XXII When Customer Satisfaction Isn’t Good Enough: The Role of Switching Incentives and Barriers Affecting Customer Behavior in Korean Mobile Communications Services........................ 351 Moon-Koo Kim, Electronics and Telecommunications Research Institute, Korea Myeong-Cheol Park, Information and Communications University, Korea Jong-Hyun Park, Electronics and Telecommunications Research Institute, Korea In communications services, the continued competitiveness and growth of a company depends vitally on customer value. In Korea’s maturing mobile market, an intense competition is under way among carriers. As the market nears the point of saturation, carriers are focusing on winning over competitors’ subscribers, at the same time on retaining their existing customers. Understanding the factors that influence customers’ switching behavior, therefore, is crucial for Korean mobile carriers’ quest for successful customer strategies. This chapter attempts to explain the relationship between customer satisfaction and customer behavior using switching incentives and switching barriers. Chapter XXIII Telecommunication Customer Demand Management . ...................................................................... 364 Jiayin Qi, Beijing University of Posts and Telecommunications, China Yajing Si, Beijing Wuzi University, China Jing Tan, Beijing University of Posts and Telecommunications, China Yangming Zhang, Beijing University of Posts and Telecommunications, China This chapter proposes a customer demand analysis method and proposes ways to capture customer demand knowledge on the basis of the customer value hierarchy model. Then, it presents a novel product recommendation approach, which involves the customer value hierarchy model into traditional recommender systems. Finally, the chapter develops a method that telecom operators can use to estimate their customer demand and respond to their demand automatically. Chapter XXIV Telecommunication Customer Detainment Management.................................................................... 379 Jiayin Qi, Beijing University of Posts and Telecommunications, China Yuanquan Li, Beijing University of Posts and Telecommunications, China Chen Li, Beijing University of Posts and Telecommunications, China Yingying Zhang, Beijing University of Posts and Telecommunications, China Jing Tan, Beijing University of Posts and Telecommunications, China This chapter proposes an integrated methodological system of telecommunication customer detainment management including the customer churn prediction and customer detainment management. It studies the formulation of customer detainment management strategy. Chapter XXV How to Plan for an Upgrading Investment in a Data Network?.......................................................... 400 Frédéric Morlot, Orange Labs, France Salah Eddine Elayoubi, Orange Labs, France

This chapter illustrates how a mobile data network operator can plan an upgrading investment to anticipate explosions of the demand, taking into account the expected profit and the customer satisfaction. The former parameter grows with the demand, whereas the latter sinks if the demand is too high, as throughput may collapse. As the equipment price decreases with time, it may be interesting to wait rather than to invest immediately. The chapter then proposes and discusses two methods that help making a decision. The first one is an actualization algorithm, where the upgrade should be performed when the loss of profit, derived analytically, exceeds the expected discount. The second is a real option-like strategy to hedge against the risk that the investment has to be anticipated. Chapter XXVI Telecommunication Investments Analysis: A Multi-Criteria Model................................................... 414 Georgios N. Angelou, University of Macedonia, Greece Anastasios A. Economides, University of Macedonia, Greece Recognizing the inadequacy of traditional quantitative cost-benefits analysis for evaluating telecommunications investments, researchers suggest real options (ROs) for controlling and valuating telecommunications business activities. However, RO models are strictly quantitative and very often telecommunications investments may contain qualitative factors, which cannot be quantified in monetary terms. In addition, ROs analysis results in some factors that can be treated more efficiently when taken qualitatively. This chapter deals with quantitative and qualitative analysis and integrates ROs and Analytic Hierarchy Process (AHP) into a common decision analysis framework providing a multi-criteria model for analyzing telecommunication investments in the deregulated business field. Chapter XXVII A Business Planning Framework for WiMAX Applications............................................................... 433 Rebecca De Coster, Brunel University, UK This chapter introduces a business planning framework which identifies generic approaches for examining the market potential for WiMAX applications in the mobile networking sector. The market potential is examined on the basis of value-based positioning within the industry sector. Positioning strategies are identified in terms of the industry value network; end-user applications and competitive strategies. The other part of the business planning framework comprises generic approaches for examining the business case which needs to be aligned with the market potential. The business case enables a cost benefit analysis by developing innovation forecasts by utilizing an open-systems view of innovation management. Chapter XXVIII Adoption of VoIP Applications in Public and Private Organizations.................................................. 447 Nicoletta Corrocher, Bocconi University, Italy and University of Tromso, Norway Roberto Fontana, University of Pavia, Italy and Bocconi University, Italy Claudia Parlanti, Bocconi University, Italy The chapter investigates the determinants of diffusion of VoIP applications in a sample of public and private organization in Italy. It first reviews the recent developments in the technology and identifies the current trends and impacts on the costs and benefits of Voice over IP (VoIP) adoption. Second, it

discusses recent policy efforts, especially at the European Union level, toward the implementation of the technology. Third, it presents the empirical investigation. Results suggest that organizations become more likely to adopt as time goes by, and that the decision to adopt is mostly affected by size and availability of financial resources. Chapter XXIX Intelligent Networking and Business Process Innovation: A Case Study Analysis of Home Box Office and Dell Computers................................................................................................ 461 Richard A. Gershon, Western Michigan University, USA This chapter examines the subject of business process innovation which involves creating systems and methods for improving organizational performance. Special attention is given to the topic of intelligent networking which represents the combination of software, technology and electronic pathways that makes business process innovation possible for both large and small organizations alike. A central tenet is that the intelligent network is not one network, but a series of networks designed to enhance worldwide communication for business and residential users. Two very different kinds of intelligent networks are discussed in this chapter. The first involves satellite-to-cable television networking where the emphasis is on program distribution to the end consumer. The second is a supply chain management network where the emphasis is on just-in-time manufacturing. Each of the said networks represents a highly innovative business process and shares the common goal of improving organizational performance. Chapter XXX Can M-Commerce Benefit from Pervasive Computing?..................................................................... 474 Stan Kurkovsky, Central Connecticut State University, USA As an application area where many principles of pervasive computing have been successfully implemented, mobile commerce has reaped significant benefits from the recent scientific and technological advances. This chapter discusses a number of pervasive computing principles and illustrates how they have been implemented in mobile commerce applications. The chapter also presents some new trends in developing context aware M-Commerce services that tap into the power of Web 2.0 services and digital communities.

Section IV Telecommunications Technology Management Chapter XXXI Basics of Telecommunication Management........................................................................................ 488 Katalin Tarnay, University of Pannonia, Hungary This chapter familiarizes the reader with the main components, functions and key terms of telecommunications management. Starting at the definition of telecommunications management, it presents the management functions, the managed objects, the management information bases and the main management protocols in a simple understandable way. Towards the end of the chapter, a simplified example on telecommunications management demonstrates the application of the theoretical material presented.

Chapter XXXII Telecommunication Management Protocols........................................................................................ 502 Katalin Tarnay, University of Pannonia, Hungary This chapter familiarizes the reader with the fundamentals of communication protocols in a special application area called telecommunications management. It presents the most widely used protocol, the Simple Network Management Protocol (SNMP), the open system management protocols, and the mobile internet management protocols for Authentication, Authorization and Accounting (AAA). Towards the end of the chapter, the chapter also provides tables to help the reader compare the management protocols presented. Chapter XXXIII Cellular Network Planning: Evolution from 2G to 4G........................................................................ 515 Marc St-Hilaire, Carleton University, Canada Samuel Pierre, École Polytechnique de Montréal, Canada This chapter presents the characteristics and the architecture of each generation of cellular networks (1G, 2G, 3G and 4G). Then, it exposes different planning problems related to each generation followed by a short description of different solutions that have been proposed in the literature.

Volume II Chapter XXXIV IP Address Management: Challenges, Solutions and Future Perspectives.......................................... 526 Faouzi Kamoun, University of Dubai, UAE IP network connectivity is becoming so important for business that it is being compared today, to basic utilities such as water and electricity. Today, more than any time before, companies are realizing the need to adopt and implement a comprehensive IP Address Management (IPAM) strategy. This chapter turns the spotlight on the most important challenges in IPAM and attempts to address some of the solutions and best practices to tackle these challenges. The chapter underlines the need for organizations to adopt proven IPAM best practices and deploy good automated IPAM tools. This will put them in a better position to expand and leverage their existing networks, while optimizing their IP address space in a secured and controlled fashion. Chapter XXXV Digital Cable TV Networks: Converging Technologies, Value-Added Services and Business Strategies........................................................................................................................ 542 Ran Wei, University of South Carolina, USA Zizhong Zhao, Communication University of China, China This chapter focuses on digital cable TV networks as a convergent network with telecommunications networks and the Internet that provides broadcasting TV and radio, telecommunications services, and

IP-based publishing and E-Commerce. The chapter first traces the technological evolution of cable TV, highlighting recent developments in digitalization and convergence. The transformation of cable TV networks from channel operators to unified platforms is discussed. Furthermore, this chapter examines the value chain and collaborative opportunities among the participants in the digital cable TV revolution. Chapter XXXVI Diffusion and Oscillation of Telecommunications Services: The Case of Web 2.0 Platforms............ 557 Tobias Kollmann, University of Duisburg-Essen, Campus Essen, Germany Christoph Stöckmann, University of Duisburg-Essen, Campus Essen, Germany Carsten Schröer, University of Duisburg-Essen, Campus Essen, Germany The diffusion of a Web 2.0 product or services is, unlike to traditional consumer or industrial goods, not only based on purchase. Full acceptance of Web 2.0 platforms occurs by recurring utilization. This chapter focuses on diffusion characteristics of this innovative category of ICT products and provides management concepts for competition. The concept of critical mass is applied to different growth scenarios. Additional success factors are discussed. Markets are never settled, due to the ever changing and oscillating conditions. The chapter shows that there is always a chance to capture a market or at least to grow against competition in a Web 2.0 setting. Chapter XXXVII The Diffusion of WiMax Technology: Hurdles and Opportunities..................................................... 571 Phillip Olla, Madonna University, USA This chapter discusses the potential of WiMax technology to deliver personal broadband and fixed Internet capabilities. The chapter applies components from the global diffusion of the Internet framework to analyze the current state of WiMax deployment utilizing the following six dimensions: pervasiveness, geographic dispersion, sectoral absorption, connectivity infrastructure, organizational Infrastructure, and sophistication of use. Chapter XXXVIII VoIP Quality and Security Issues for Consumers and Small Businesses............................................. 588 David Bell, Pacific Union College, USA Sunil Hazari, University of West Georgia, USA VoIP is the use of Internet protocols to provide telephone services that have previously been delivered over traditional telephone networks. Advantages of VoIP include cost, portability, and functionality which are the main reasons that many consumers and small businesses are considering this technology as a replacement to traditional telephone services. There are however risks associated with VoIP services which impact quality and security of the phone system for voice communications. This chapter reviews issues related to quality and security faced by consumers and small businesses. Recommendations are provided to improve call quality and mitigate threats faced in the VoIP environment.

Chapter XXXIX Emerging Security Issues in VANETS for E-Business........................................................................ 599 S. S. Manvi, REVA Institute of Technology and Management, India M. S. Kakkasageri, Basaveshwar Engineering College, India The deployment of VANETs for E-Business is rapidly approaching, and their success and safety will depend on viable security solutions acceptable to consumers, manufacturers and governments. This chapter presents the emerging security issues in Vehicular Ad hoc Networks (VANETs) for E-Business along with some of the solutions. Security issues discussed are authentication, trust, confidentiality, non-repudiation and detection of malicious users. Chapter XL Telecommunications Network Planning and Operations Management in an Academic Environment: The Case Study of the Aristotle University of Thessaloniki......................................... 615 Sotirios K. Goudos, Aristotle University of Thessaloniki, Greece Angeliki Z. Agorogianni, Aristotle University of Thessaloniki, Greece Zaharias D. Zaharis, Aristotle University of Thessaloniki, Greece Network planning and management in a large organization like a university is a complex task. A large university is an inherently demanding environment in terms of telecommunications services offered and technologies used. This chapter presents and discusses network management and planning issues in the Aristotle University of Thessaloniki, Greece. Examples of network management procedures are given. It presents the data model for service provision. The network expansion and cost reduction case studies are discussed. A SWOT analysis about University’s Telecommunications Center is given. Finally, it discusses the migration analysis for future upgrades that will fully enable the use of emerging technologies such as Voice over IP (VoIP). Chapter XLI Planning of Wireless Community Networks........................................................................................ 634 Károly Farkas, University of West Hungary, Hungary Csaba A. Szabó, Budapest University of Technology & Economics, Hungary Zoltán Horváth, Budapest University of Technology & Economics, Hungary This chapter discusses the applications, state-of-the-art technologies, planning methods and business models for wireless community networks, and provides an integrated presentation of these essential parts with examples. It gives an overview about the state-of-the-affairs of wireless community networks presenting the driving forces, stakeholders, and services built upon applications in some carefully selected projects. Then, it discusses the technological aspects and suggests a design methodology for planning wireless community networks. The application of this methodology is illustrated via an ongoing digital city project in Hungary. Chapter XLII Human Factors for Business Mobile Systems..................................................................................... 653 David Golightly, University of Nottingham, UK

This chapter addresses an area of science, human factors, with particular relevance to developing and deploying business mobile systems that are fit for purpose. The value of human factors is discussed, before moving onto some general guidelines to ensure that a mobile technology is suitable for its users. It is critical to take an approach that puts users at the heart of requirements, build and deployment of a new technology or service. This approach is presented as a three-stage model of context analysis, specification and design, and evaluation.

Section V Telecommunications Technology and Applications Chapter XLIII Towards QoS-Inferred Internet............................................................................................................ 672 Mohamed Boucadair, France Telecom-Orange Labs, France Pierre Levis, France Telecom-Orange Labs, France Pierrick Morand, France Telecom-Orange Labs, France IP networks are the federative transport networks for a large set of emerging services. These services demand hard guarantees in term of the service availability, experienced Quality of Service (QoS) and robustness. In order to meet QoS requirements of these services in an inter-domain context, several issues should be solved. This chapter focuses on two issues: provider-to-provider agreements and enhancements to inter-domain routing protocol to convey QoS-related information. This chapter provides a framework suitable for the promotion of QoS-enabled services with an inter-domain scope: the Parallel Internet. This concept is a viable way for the management of IP resources so as to deliver end-to-end QoS-enabled services. Chapter XLIV The Playout Control Management: An Issue for the IP Telephony Service Providers........................ 689 Mirko Luca Lobina, Università di Cagliari, Italy Luigi Atzori, Università di Cagliari, Italy Fabrizio Boi, Università di Cagliari, Italy This chapter proposes technical playout control management and planning strategies and compares the strategies IP Telephony Service Providers can choose with the aim of saving money and offering a better quality of service. The chapter also introduces the state-of-the-art quality index for IP Telephony and provides the reader with examples on some economic scenarios of IP Telephony. Chapter XLV Open APIs and Protocols for Services and Applications in Telecoms................................................. 703 Nikolaos D. Tselikas, University of Peloponnese, Greece Georgia M. Kapitsaki, National Technical University of Athens, Greece Dimitrios G. Makris, University of Peloponnese, Greece Iakovos S. Venieris, National Technical University of Athens, Greece

This chapter discusses the role of open APIs and protocols for advanced service provisioning and the corresponding state of the art. Specifically, the role and the trade-offs in modern telecoms between open APIs and Protocols, that is OSA/Parlay APIs, JAIN APIs and SIP, are discussed. A technical implementation analysis for each solution is presented, based on a call-related service, in order to set a common basis for the aforementioned technologies, since “voice” is a common denominator for a Fixed or Mobile Operator or an Internet Service Provider. A performance evaluation study regarding the implemented services is also presented. Chapter XLVI On the Management Performance of Networked Environments Using Web Services Technologies.......................................................................................................................... 724 Lisandro Zambenedetti Granville, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Ricardo Neisse, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Ricardo Lemos Vianna, Federal University of Rio Grande do Sul – Porto Alegre, Brazil Tiago Fioreze, Federal University of Rio Grande do Sul – Porto Alegre, Brazil This chapter provides a comparison between different strategies of integrating conventionally managed network devices into Web Services-based management processes. Such integration is important because it allow devices to be controlled from the IT perspective using Web Services technologies. Integration approaches are evaluated in terms of network traffic and response, since these are two of the most aspects of network management solutions. Chapter XLVII Automated Fault Management in Wireless Networks ........................................................................ 742 Raquel Barco, University of Málaga, Spain Pedro Lázaro, University of Málaga, Spain In the near future, several radio access technologies will coexist in Beyond 3G mobile networks (B3G) and they will be eventually transformed into one seamless global communication infrastructure. Selfmanaging systems (i.e. those that self-configure, self-protect, self-heal and self-optimize) are the solution to tackle the high complexity inherent to these networks. In this context, this chapter proposes a system for automated fault management in the Radio Access Network (RAN) of wireless systems. The chapter presents some basic definitions and describes how fault management is performed in current mobile communication networks. Some methods proposed for auto-diagnosis, which is the most complex task in fault management, are also discussed. The proposed systems are based on the analysis of Key Performance Indicators (KPIs) in order to identify the cause of the network malfunction. The theory is supported by results obtained from trials in real wireless networks. Chapter XLVIII Modeling Intrusion Detection with Self Similar Traffic in Enterprise Networks . ............................. 760 Cajetan M. Akujuobi, Prairie View A & M University, USA Nana K. Ampah, Prairie View A & M University, USA

Most of the existing networks (e.g., telecommunications, industrial control, enterprise networks etc.) have been globally connected to open computer networks (Internet) in order to decentralize planning, management and controls in business. Most of these networks were originally designed without security considerations, thereby making them vulnerable to cyber attacks. This has given rise to the need for efficient and scalable intrusion detection systems (IDSs) and intrusion prevention systems (IPSs) to secure existing networks. It has been proven that the right combination of security techniques always protects networks better. The novelty of our proposed IDS technique presented in this chapter lies in its efficiency and ability to eliminate most of the limitations of existing IDSs and IPSs, thereby ensuring high level network protection. Chapter XLIX High-Speed Multimedia Networks: Critical Issues and Trends........................................................... 775 Dimitris Kanellopoulos, University of Patras, Greece This chapter presents high-speed networking technologies and standards such as ATM, Fast Ethernet, 10 Gigabit Ethernet, SONET, RPR, PBT, PBB, T-MPLS and Optical Transport Network (OTN). It considers the requirements imposed to high-speed networks by multimedia applications and analyses crucial issues of high-speed networking such as bandwidth problems, discarding policies and fast broadcast. Chapter L Emerging Telecommunications Technologies: Cognitive Radio......................................................... 788 J. Joaquín Escudero-Garzás, University Carlos III de Madrid, Spain Ana García-Armada, University Carlos III de Madrid, Spain This chapter introduces the novel concept of Cognitive Radio for wireless telecommunications. Cognitive radios are a new type of radio devices that include cognition and reconfigurability features. This chapter presents the reader the new paradigm that cognitive radio networks have created. It focuses on the challenges in PHY layer and MAC sublayer and the most relevant studies in these fields. Chapter LI Game Theory for PHY Layer and MAC Sublayer in Wireless Telecommunications......................... 804 J. Joaquín Escudero-Garzás, University Carlos III de Madrid, Spain Ana García-Armada, University Carlos III de Madrid, Spain This chapter addresses the role of Game Theory for wireless communications. It introduces Game Theory and its fundamentals, and gives an overview of the applications of Game Theory in the wireless networks for PHY layer and MAC sublayer. Chapter LII Agent Based Product Negotiation Models in Mobile Commerce....................................................... 820 S. S. Manvi, REVA Institute of Technology and Management, India L. B. Bhajantri, Basaveshwar Engineering College, India Mobile commerce is an emerging manifestation of electronic commerce that bridges the domains of Internet, mobile computing and wireless telecommunications in order to provide an array of sophisticated

services to mobile users. This chapter brings out various issues in M-Commerce and describes various agent based product negotiation models in mobile commerce environment. The negotiation models discussed are based on auctions, trade off, argumentation, contract Net, bilateral and game theory. Chapter LIII Role of Telecommunications in Precision Agriculture........................................................................ 836 James M. McKinion, USDA-ARS, USA Precision agriculture has been made possible by the confluence of several technologies: geographic positioning systems, geographic information systems, image analysis software, low-cost microcomputer-based variable rate controller/recorders, and precision tractor guidance systems. While these technologies have made precision agriculture possible, there are still major obstacles which must be overcome to make this new technology accepted and usable. Most growers will not do image processing and development of prescription maps themselves but will rely upon commercial sources. There still remains the challenge of storage and retrieval of multi-megabytes of data files for each field, and this problem will only continue to grow year by year. This chapter discusses the various wireless technologies which are currently being used on three proof-of-concept farms or areas in Mississippi, the various data/information intensive precision agriculture applications which use wireless local area networking and Internet access, and the next generation technologies which can immensely propel precision agriculture to wide spread use in all of agriculture.

Section VI Telecommunications Network Design Chapter LIV Network Planning and Dimensioning for Broadband Access to the Internet Regarding Quality of Service Demands................................................................................................................ 852 Franz Hartleb, T-Systems, Germany Gerhard Haßlinger, T-Systems, Germany Sebastian Kempken, University of Duisburg-Essen, Germany An ongoing challenge in telecommunication is the integration of a variety of services on broadband access platforms at increasing transmission speed. While broadband access is established as standard equipment for homes, the networking capacities in the access and the backbone are steadily extended to keep pace with higher traffic volumes. The chapter focuses on planning and traffic engineering for link bandwidth and buffers as main resources in communication platforms based on measurement and statistical properties of traffic growth and variability. The chapter summarizes quality of service demands of main Internet applications and mechanisms to control and stabilize the performance of ISP network platforms on different time scales. Load thresholds for link dimensioning are derived with regard to quality of service (QoS) demands and the variability in source and aggregated profiles. Finally, link level and network wide traffic engineering is addressed together with load balancing techniques.

Chapter LV Overlay Networks: New Techniques for Global Service and Network Provisioning.......................... 867 Gerhard Haßlinger, T-Systems, Germany Service and content delivery over the Internet is currently supported by overlay architectures of different types. There is a trend towards distributed computing and service creation in peer-to-peer and grid networks, which are able to overcome performance bottlenecks of client server architectures. Overlays are deployed for single applications or as multi purpose infrastructure for communities with focus on their special demands. Various overlay structures have also developed on lower network layers. The motivation for those overlays is to bridge or extend one networking technology on top of another in order to build common widespread platforms through heterogeneous telecommunication environments. This chapter addresses such approaches especially within the standardization of Internet Protocols (IP), where the main focus is on evolving techniques on higher layers. Chapter LVI Optimising P2P Networks by Adaptive Overlay Construction............................................................ 882 James Salter, University of Surrey, UK Nick Antonopoulos, University of Surrey, UK Distributed Hash Tables (DHTs) have been used in Peer-to-Peer networks to provide query lookups in typically O(log n) messages whilst requiring maintenance of only small amounts of routing state. This chapter proposes ROME, a layer which runs on top of the Chord DHT to provide control over network size through monitoring of node workload and proposes the use of processes to control the addition or removal of nodes from the network. This chapter shows that this technique can reduce further the hop counts in networks where available node capacity exceeds workload, without the need to modify any processes of the underlying Chord protocol. Chapter LVII Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier....................... 895 Susan J. Chinburg, Rogers State University, USA George Scheets, Oklahoma State University, USA The network carrier must utilize the full potential of existing physical infrastructure before any new investments can be considered. Much work has been done to develop optimal design methodologies that generate a “best” design but designs often have to be changed to meet operational considerations, potentially mitigating any optimization benefits. This chapter proposes to expand the optimal network design process by applying a process borrowed from Finance and Operations Research/Management Science literature known as the Efficient Frontier or production frontier analysis. By comparing any subsequent design to the frontier, the network designer can have an understanding of the impact of changes in the design strategy to the long-term cost effectiveness. Chapter LVIII Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS................. 909 Mohamed Zaki, Azhar University, Egypt Salah Ramadan, Azhar University, Egypt

The cellular principle is an effective way to guarantee efficient utilization of the offered radio band. Although PCS networks use the cellular principle, the next generation of PCS networks needs more improvements in location management to face the increased number of users. Both an Enhanced ProfileBased Strategy (EPBS) for small-scale roaming and a Caching Two-Level Forwarding Pointer (C2LFP) strategy for large-scale roaming have been proposed. This chapter introduces a model that unites the above two strategies; the idea behind this model is based on applying those two location management strategies, and specifying the physical parameters of PCS networks from mobility management’s point of view; so that the underlying solutions can be more cost effective for location management. The results have been obtained from a case study are presented in order to provide a deep explanation of the proposed integration approach. Chapter LIX Secure Resource Optimization in Distributed Service Computing...................................................... 927 Kaiqi Xiong, Texas A&M University, USA Harry Perros, North Carolina State University, USA This chapter considers a set of computer resources used by a service provider to host enterprise applications for customer services subject to a service level agreement (SLA). The SLA defines three QoS metrics, namely, trustworthiness, percentile response time and availability. The chapter first gives an overview of current approaches, solutions and challenges in the security-aware resource optimization problem. Then, it presents a framework for solving the problem. Chapter LX Trends, Optimization and Management of Optical Networks............................................................. 941 Jadranka Skorin-Kapov, Stony Brook University, USA Darko Skorin-Kapov, Adelphi University, USA This chapter provides a review of optical networking, its current issues, trends, and ways to efficiently design and manage a wide range of optical networks. The overview of optical networking includes its current capabilities, placement of ‘special equipment’ nodes and components, and design of network topology. Efficient management and utilization of geographically different networks (such as wide area networks, metro networks, and access networks) present different optimization problems dealing with the placement of special optical equipment. Current algorithmic approaches are summarized, and possibilities for further research are suggested.

Compilation of References................................................................................................................ 957

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Foreword

Introduction For 30 years I taught graduate courses, consulted for many companies and governments around the world, and did research in the area of information systems and telecommunications as well as spending several years as the CIO of a telecommunications company. I wish I had this book to provide the valuable data, information, knowledge, recommendations, experiences and guidance contained herein for all those activities. We live in the age of communications and the policies, regulations, technologies, services, economics, infrastructure, planning, design and end user demands throughout the worldwide telecommunications industry produce forces that are now pushing the industry forward at a rapid pace. The end user’s demand for more bandwidth; increased reliance on mobility services; desire for better security and privacy, and the end users’ assessment of cost versus performance are driving the providers, regulators, researchers, and policy makers to reassess all aspects. Thus far, the industry has reacted to these forces driving major infrastructure and technological change through consolidation, as carriers merge and equipment suppliers struggle to survive. Both on the domestic and international levels, regulators and government agencies are struggling to cope with rapid, profound changes in an industry that had been predictable for more than 100 years. The technologies underlying the industry’s changing infrastructure can be summed up as: IP transport’s ability to merge voice, video and data; the long-haul fiber glut and the resulting reduction in the cost of bandwidth; the wide variety of local broadband wired and wireless solutions; and increasing security requirements; especially the ability to protect users on the Internet. The telecommunication’s industry is riding the crest of worldwide demand for new video-enabled services.  The emergence of video as a major force is reshaping mobile and fixed line telecommunications by the investment of large sums of money into new infrastructure which will cause a new telecommunication’s landscape to be shaped. This new landscape will be formulated around the following 6 components: 1. 2. 3. 4. 5. 6.

Telecommunications Policy Telecommunications Industry Telecommunications Business Management Telecommunications Technology Management Telecommunications Technology and Applications Telecommunications Network Design

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This handbook presents empirically-based evidence that provides valuable information and knowledge along with recommendations for the participants in each of these components.

Telecommunications Policy For policy makers, regulators, and legislators around the world, this book provides invaluable data and recommendations that will help them deal with policies related to the tremendous growth in telecommunications and the demand for new, high performance services. Regulators in many countries are finding that existing regulatory frameworks are not suitable for dealing with these new services and related technologies. A framework in this section of the book is presented that is comprised of five major components: consumer and intellectual property protection, market and resources access, and environmental protection. New and innovative approaches are discussed in many chapters related to these issues. Since wireless/mobile technologies are currently at the center of many policy and regulatory issues suggested reforms in the radioelectric spectrum management mechanisms and rational assignment and use of the radion spectrum are discussed in several chapters of this section. The role of regulation on incentives to invest in telecommunications in Europe, Australia, and the United States, especially in Next Generation Access Networks (NGA), is presented in both quantative as well as qualitative terms. Policy makers and regulators around the world will find this section highly useful.

Telecommunications Industry The telecommunications industry is undergoing changes that have an effect on revenues, costs, market share, profitibality, competition, planning, efficiency, operations, personnel, and management practices. This section of the book provides extremely useful data, information, knowledge, and innovative insights into these topics. The convergence of IT and telecommunications and the emergence of new technologies and new entrants with new business models are discussed in several chapters of this section of the book. The local exchange telephone market is no longer considered to be a natural monopoly as a result of technological advancements. Digital technology has enabled traditional telecommunications companies to transition their network architecture from one based on copper wires and circuit switches for providing high quality transmission of point-to-point voice signals to a multi-faceted, general network based on fiber optic cables and packet switches capable of providing an array of voice, data, and video services. As noted in one chapter, convergence is fundamentally changing the nature of what it means to be a telecommunications company. One example of the impact of convergence presented in this section is what is happening in Korea. In Korea, the home network industry has been the object of great expectations among the government and business community. Thus far, however, it has proved unable to fulfill these expectations. On the basis of analyses, this chapter offers policy suggestions from a digital convergence perspective to help remove the obstacles to business cooperation among the participant industry sectors of the home network industry. Managerial implications for the participating firms are discussed in terms of adopting a new business model framework. The Internet has developed into a global network enabling users worldwide to connect to each other to exchange information and data. The initial peering arrangements have generally been replaced by commercial transit arrangements, as backbone providers seek to recoup their network infrastructure investments and generate commercial profits. This

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is a key cause of the issues and debates that have emerged between developed and developing countries about international Internet interconnection services (IIS). This book presents data on current interconnection settlement arrangement models that disfavor ISPs and end-users in the Asia-Pacific region and summarizes the main current IIS issues between the Asia-Pacific and Western regions. As part of the industry analysis the book presents a techno-economic analysis of Mobile Virtual Network Operators by examining cross-national data in order to identify possible factors related to the observable patterns of Mobile Virtual Network Operator (MVNO) penetration including an economic assessment of market structure and environment for different countries’ MVNO penetration. Fiber optics forms one of the industry’s pivotal telecommunications technologies of the global economy, offering greater speed and security than other modes. Fiber’s role in contemporary urban restructuring is discussed. One chapter in the book analyzes and discusses the spatial distribution of the world’s fiber lines, noting major transatlantic and transpacific markets and newer systems. The enormous construction boom of the 1990s and early 2000s which led to severe overcapacity, with significant economic fallout is presented. One chapter in the book analyzes the role of non-market actions (NMA’s) in firms’ competitive position within the European mobile telecommunications industry. The bases of non-market actions are reviewed and classified as well as the use of non-market actions by the mobile phone operators is described using a particular case to describe the relationship between the use of legal actions and the first mover advantage in the European mobile telecommunications industry.

Telecommunications Business Management Having taught courses and performed research in the area of telecommunications and information systems for a major university for over 30 years, it was quite a transition when I became the Chief Information Officer (CIO) for a Telecommunications company and discovered the “business” of telecommunications. This book provides a number of extremely useful chapters on the business management aspects of telecommunications which I wish I had read before having to learn it on the job. Telecommunications is a business that has many aspects that traditional business and planning models do not encompass. One example of trying to deal with some of the idiosyncratic aspects of the telecommunication’s business is the chapter that examines an implementation of an Activity-based Costing (ABC) system in a Portuguese telecommunications firm called Marconi. It is argued that they changed its management accounting system due to efficiency and institutional pressures from its constituencies, namely the Portuguese telecommunications regulators, its managers, and its competitors following the liberalization of the Portuguese and European Union telecommunications market. A chapter examines business process innovation which involves creating systems and methods for improving organizational performance and the interesting and innovative topic of intelligent networking which represents the combination of software, technology and electronic pathways that makes business process innovation possible for both large and small organizations based on the central tenet that an intelligent network is not one network, but a series of networks designed to enhance worldwide communication for business and residential users. Other chapters focus on the internationalization processes of national telecommunications companies (telcos) which have moved from a domestic monopoly to a player within the global industry. Every organization has a culture which guides its policies and management principles and can not be ignored. Several chapters in the book present data on the importance of organizational culture for the management of any organization, the theoretical link between organizational culture, and a variety of

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variables which affect organizational performance and efficiency, directly and indirectly. Such variables are knowledge management, organizational climate, leadership, quality, innovation and entrepreneurship, human resource management, and employee behavior. Planning is essential for any organization and is especially important in a fast changing industry such as telecommunications. Planning and operational management models are presented in several chapters of this section of the book which encompass business strategies, knowledge management, customer satisfaction, customer demand, churn reduction, cost-benefit analysis, investment analysis, upgrade strategies, adoption of new technologies (such as VoIP), convergent technologies, and human factors. These are discussed in the context of various countries, technologies, and business domains including academia.

Telecommunications Technology Management Telecommunications is functionally dependent on a wide array of technologies. These technologies have been changing at a rapid pace thereby producing an array of technological issues that have placed a greater emphasis on managing these technologies. This book presents empirical data as well as theory-based accounts related to managing the many issues created by these new technologies. For example, the diffusion of a Web products or services is unlike traditional consumer or industrial goods but is characterized by recurring utilization and the permanent supervision of a platform regarding its compliance with qualitative, as well as ethical and legal standards. Web Services technologies enable the proper communication of processes deployed in quite hostile environments such as the Internet. Cellular networks have experienced significant changes over the last few years. In order to keep up with this constant evolution, planning tools must also adapt themselves in order to reflect the particularities and architecture of each generation. Voice over IP or VoIP is the use of Internet protocols to provide telephone services that have previously been delivered over traditional telephone networks. Advantages of VoIP include cost, portability, and functionality as a replacement to traditional telephone services but as pointed out in several chapters there are risks associated with VoIP services which impact quality and security of the phone system for voice communications. The chapter on the basics of technology management focuses on management functions, the managed objects, the management information base, and the management protocols. The fundamentals of communication management protocols have changed with the most widely used protocol, the Simple Network Management Protocol (SNMP) but new open system management protocols and the mobile internet management protocols are used for Authentication, Authorization and Accounting (AAA). One chapter in this section points out that IP network connectivity is becoming as important for businesses as basic utilities. IP addresses are among the most important resources to be managed. Ready access and flawless handling of IP address usage, assignment, tracking and reallocation help in enhancing network reliability and security, while enabling more efficient network expansion and troubleshooting. The chapter on managing IP Addresses is the best one on this subject that I have ever read. The chapter, “Planning of Wireless Community Networks”, discusses the applications, state-of-the-art technologies, planning methods and business models for wireless community networks and provides an integrated presentation of these essential parts with examples which is invaluable for managing a wireless network.

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Telecommunications Technology and Applications Technologies are useless until utilized for some application. Telecommunication organizations invest large sums of money in technologies with the assumption that they will receive a return on that investment based on how it is applied to provide services that generate revenue and/or reduce costs. But applying technologies for such purposes is filled with problems. The section of the book “Telecommunications Technology and Applications” discusses in a rather complete manner the problems and issues faced by providers in using technologies and especially new technologies for new and improved applications. The utilization of service and content delivery over the Internet is currently supported by overlay architectures of different types. There is a chapter which focuses on two issues related to IP, federated networks, namely: provider-to-provider agreements and enhancements to inter-domain routing protocols to convey QoS-related (Quality of Service-related) information. A concept called Meta-QoS-Class is introduced together with an enriched version of the Border Gateway Protocol. The chapter on the use of Web Services for management describes how Web Services allow the integration of low-level activities (e.g., retrieving monitoring information from gateways) with high-level business processes (e.g., creating a new product and its marketing strategy.). Despite clear advantages, Web Services-based management does not come for free; since Web Services are based on XML documents, its performance, compared with traditional management technologies, may represent an important drawback. The chapter on intrusion detection notes that most existing networks have been globally connected to open computer networks (Internet) in order to decentralize planning, management and controls in business but most of these networks were originally designed without security considerations, thereby making them vulnerable to cyber attacks. This has given rise to the need for efficient and scalable intrusion detection systems (IDSs) and intrusion prevention systems (IPSs) to secure existing networks which are discussed in detail. Fault management is presented as systems that are based on the analysis of Key Performance Indicators (KPIs) in order to identify the cause of network malfunctions. The chapters on m-based (Mobile based) commerce and pervasive computing and the use of agent technologies reveals many hidden issues in various applications. The discussion of a novel concept called Cognitive Radio for wireless telecommunications is fascinating. Cognitive radios are a new type of radio device that include cognition and reconfigurability features, thus creating a new paradigm for wireless environments. A chapter also describes the creative use of game theory for PHY layer and MAC sub-layer in Wireless Telecommunications. The chapter on high-speed multimedia networks: critical issues and trends is a very complete coverage of the range of technologies and standards ranging from Asynchronous Transfer Mode (ATM) and Fast Ethernet to Multi Protocol Label Switching (T-MPLS) and Optical Transport Network (OTN). Chapters on Open API and protocols as well as security concerns are well worth reading. The chapter on the role of telecommunications in Precision Agriculture illustrates how an application typically requires the convergence of several technologies to make the application a success. Since most farms are by definition rural and do not have high speed access to the Internet, the problem of moving 10’s, 100’s and even 1000’s of megabytes of essential information and data must be solved to help make precision agriculture easy to use and even transparent to the grower. Wireless technology can fill this gap and help make precision agriculture the standard in the future.

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Telecommunications Network Design Having taught courses on network design and having been involved in designing several networks including a commercial DSL network, I could have benefitted from the chapters in this section of the book. In designing the DSL network, we had to utilize existing network facilities of an incumbent wireline company. Several chapters in this section emphasize that the network carrier must utilize the full potential of existing physical infrastructure before any new investments can be considered. There is a trend towards distributed computing and service creation in peer-to-peer and grid networks, which are able to overcome performance bottlenecks of client server architectures but these are not without issues that must be planned for and tested. One chapter focuses on planning and traffic engineering for link bandwidth and buffers as main resources in communication platforms based on measurement and statistical properties of traffic growth and variability which are critical for managing these technologies. Much work has been done to develop optimal design methodologies that generate a “best” design but designs often have to be changed to meet operational considerations, potentially mitigating any optimization benefits. One chapter in this section proposes to expand the optimal network design process by applying a process borrowed from Finance and Operations Research/Management Science literature known as the “Efficient Frontier” or production frontier analysis. Using this idea, a portfolio of designs differing in cost, and number, size and location of nodes will be developed and from that the efficient frontier defined. By comparing any subsequent design to the frontier, the network designer can have an understanding of the impact of changes in the design strategy to the long-term cost effectiveness. As one chapter notes; the cellular principle is an effective way to guarantee efficient utilization of the offered radio band and although PCS networks use the cellular principle, the next generation of PCS networks needs more improvements in location management to face the increased number of users. Both an Enhanced Profile-Based Strategy (EPBS) for small-scale roaming and a Caching TwoLevel Forwarding Pointer (C2LFP) strategy for large-scale roaming are introduced. An evolutionary method, using a constraint Genetic Algorithm (GA) has been handled to achieve network parameters optimization and is presented in a case study format. A chapter in this section presents optimizing P2P Networks through adaptive overlay construction. Another chapter in this section presents a framework for solving a security-aware resource optimization problem under the SLA constraints of .trustworthiness, percentile response time and availability using an efficient numerical procedure. The chapter on “Trends, Optimization and Management of Optical Networks” reviews optical networking, its current issues, trends, and ways to efficiently design and manage a wide range of optical networks. Efficient management and utilization of geographically different networks (such as wide area networks, metro networks, and access networks) present different optimization problems dealing with the placement of special optical equipment whose solutions are summarized in terms of current algorithmic approaches and suggest possibilities for further research.

Summary I highly recommend this book for professors teaching courses and performing research in network management, network analysis and design, network protocols, network regulations and standards, wireless networks, network performance metrics, telecommunication services, and network security. I would also recommend it to Masters and PhD students looking for ideas for a thesis.

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For those working in the telecommunication industry whether it is at the operational level, managerial level or executive level, this book can provide solutions and approaches to existing problems as well as generate new approaches to services, control, and measuring performance. Likewise, anyone involved in networking at almost any level can benefit from one or more chapters of this book to provide a more responsive, efficient, secure, and service-oriented telecommunications network. This book is a must for policy makers and regulators around the world starting the FCC in the United States to the appropriate bodies in Australia, United Kingdom, European Union nations, countries in the Far East such as China, and countries in the Middle East. The empirical data, creative analysis, and innovative recommendations for policy and regulation of this rapidly changing and high impact area affecting the social and political aspects of every country in the world are captured in this book.

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Preface

Over the last decade the telecommunications industry has experienced rapid transformation. Many factors, such as digital convergence, wireless networks, deregulation, and globalization, have contributed to this transformation. Convergence across telecommunications and the Internet has caused major upheavals in the value chain of the telecommunications industry. Telecommunications convergence coupled with deregulation has created numerous opportunities and challenges for both incumbent telecom operators and new entrants. The convergence has put telephone companies in a fierce competition with cable TV operators for voice, data, and video services. Telephone companies are transforming their provision of voice and other broadband services to the Internet layered fiber-optic networks to embrace the IP-based telecommunications convergence. While some telecom operators build new networks, other operators offer services with networks of incumbent operators. The competition among these incumbents and new entrants will become fiercer in the future, and telecommunications planning and management become more important for telecom managers. Among stakeholders, governments had a major impact on the industry’s structure and competition through policies on licensing, mergers/acquisitions, and other regulations. Policy makers face challenges of facilitating competition into quasi-monopolistic markets, and at the same time, developing favourable conditions for the capital investments needed to sustain and improve the network infrastructure (Bauer and Bohlin, 2008). For emerging industries such as the mobile services industry, regulators have to deal with a wide variety of stakeholders. Further, as mobile technology operates in a dynamic environment and undergoes rapid changes, regulatory definitions become a moving target which implies that regulators should constantly acquire industry-specific knowledge over time (Tallberg et al., 2007; Ubacht, 2004). Consequently, regulation for the mobile industry becomes an extremely complex and involved undertaking for all stakeholders. One of the most significant developments in the telecommunication technologies of the past decade is wireless networks. The wireless network industry is evolving at a very fast pace. The diffusion of mobile handsets and services has achieved spectacular growth in many countries around the world. WiMax and Wi-Fi have shown the potential to be a leading technology in the wireless industry for the service providers. While the third generation networks are deployed, the next generation networks are developing. The key feature of the next generation is an integration of different access networks (HSDPA, UMTS, LTE, GSM, Wi-Fi, Wi-Max, etc.) around a common IP. The telecommunication market is shifting from a stable market to an increasingly user-driven market place. The telecom operators must have the ability to rapidly develop, deploy, and manage services to meet customers’ dynamically changing needs. The success of a telecom operator depends on the operator’s ability to understand and manage the organizational variables such as knowledge management, organizational climate, leadership, service quality, innovation and entrepreneurship, human resource management, and employee attitude.

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According to the U.S. Bureau of Labor Statistics (BLS), jobs in telecommunications are projected to grow faster than other occupations in the coming years. The incredible growth of telecommunications technology and the demand for a new generation of telecommunications employees, managers, and leaders facilitated the offering of Telecommunications Management programs in many higher education institutions in the United States and around the world. Although new technologies and models are continually appearing, it is high time to take stock of the new knowledge in telecommunications planning and management. The Handbook of Research on Telecommunications Planning and Management for Business provides a repository for government policy-makers, researchers, and industry practitioners to share and exchange their policy and research ideas, theories, practical experiences, discuss challenges and opportunities, and present tools and techniques in all aspects of telecommunications planning and management. This book is composed of 60 chapters and divided into 6 segments: Section I, Telecommunications Policy, which discusses various issues and recommendations for policy-makers and regulators in the telecommunications industry; Section II, Telecommunications Industry, which addresses competition, dynamics, and trends in the industry; Section III, Telecommunications Business Management, which discusses various business management topics such as organizational culture, management methods, customer management, investment, and practices; Section IV, Telecommunications Technology Management, which presents various technology management methods and techniques for security, protocol management, and new technology services; Section V, Telecommunications Technology and Applications, which addresses the state-of-the-art technologies, protocols, Web services, and implementation issues faced by telecom service providers; and Section VI, Telecommunications Network Design, which discusses methods, issues, and new trends in the network design . A brief introduction of each chapter follows. Section I: Telecommunications Policy, consists of 6 chapters. Chapter I, “Static and Dynamic Efficiency in the European Telecommunications Market: The Role of Regulation on the Incentives to Invest and the Ladder of Investment” by Walter Distaso, Imperial College (UK), Paolo Lupi, AGCOM (Italy), and, Fabio Manenti, University of Padua (Italy), provides evidence of the effectiveness of European national regulatory authorities in applying the basic principles of the ladder of investment. The analysis discusses and compares the regulatory approach adopted in 12 European countries from January 2005 to July 2007. Chapter II, “Is Regulation a Roadblock on the Information Highway?”, by James E. Prieger and Daniel Heil, Pepperdine University (USA), covers the theoretical and empirical impacts regulation has on innovation. It presents empirical evidence that regulation dampens firms’ incentive to innovate in the telecommunications industry in general and the market for broadband Internet access in particular. Both product and process (cost reducing) innovations are discussed. Chapter III, “Reforms in Spectrum Management Policy” by Claudio Feijóo, Universidad Politécnica de Madrid (Spain); José Luis Gómez-Barroso and Asunción Mochón, Universidad Nacional de Educación a Distancia (Spain), presents the reforms in the radioelectric spectrum management mechanisms that are currently being drafted (or that are even being applied). In particular, the chapter assesses three major changes that are being considered: authorisation of the secondary market, usage of auctions for primary allocation, and full liberalisation of spectrum usage. Chapter IV, “Next Generation Access Networks and their Regulatory Implications” by Ricardo Gonçalves and Álvaro Nascimento, Universidade Católica Portuguesa (Porto) (Portugal), reviews the current discussion surrounding Next Generation Access networks (NGAs) and discusses some of the main regulatory challenges. Chapter V, “The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry” by Carol C. McDonough, Univer-

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sity of Massachusetts Lowell (USA), discusses the impact of government on the market structure of the wireless industry which is regulated by the federal government. Chapter VI, “Shaping Regulation in the Australian Mobile Industry” by Indrit Troshani and Sally Rao Hill, University of Adelaide (Australia), employs qualitative evidence to investigate how regulation and legislation can affect mobile services in the Australian mobile telecommunications industry and proposes an innovative regulatory framework based on a co-regulatory approach. Section II: Telecommunications Industry, consists of 9 chapters. Chapter VII, “Analyzing the Disruptive Potential in the Telecommunications Industry” by Stefan Hüsig, University of Regensburg (Germany), covers the ex ante analysis of potential disruptive technologies. In this chapter, the theory of disruptive technology, the concept of disruptive potential and a method for applying this concept in a telecommunications planning and technology management context is presented. Chapter VIII, “Convergence of the Internet and Telecommunications” by John B. Meisel and Timothy S. Sullivan, Southern Illinois University Edwardsville (USA), provides a framework to explain the convergence of communications networks and analyzes key issues that confront public policymakers. One key competition issue, termed network neutrality, addresses the concern that the evolving broadband network architecture will enable network providers to favor the provider’s services or affiliated services at the expense of independent rivals. Chapter IX, “International Internet Interconnection Service in Asia-Pacific Region” by Moon-Soo Kim, Hankuk University of Foreign Studies (South Korea), focuses on current interconnection settlement arrangement models that disfavor ISPs and end-users in the Asia-Pacific region. After reviewing the Internet market and digital divide in the region, the chapter discusses the main current IIS issues between the Asia-Pacific and Western regions into 3 categories of concern: inequity, anticompetitive practices, and the threat of the “balkanization” of the Internet. Chapter X, “A Techno-Economic Analysis of Mobile Virtual Network Operators” by Dong Hee Shin, Penn State University Berks Campus (USA), examines cross-national data in order to identify possible factors related to the observable patterns of Mobile Virtual Network Operator (MVNO) penetration. The study conducts an economic assessment of market structure and environment for different countries’ MVNO penetration. Chapter XI, “Evolving Value Networks and Internationalization of National Telecommunication Companies from Small and Open Economies” by Riku Laanti, Fred McDougall, and Georges Baume, The University of Adelaide (Australia), focuses on the internationalization processes of national telecommunications companies (telcos) from small and open economies (SMOPECs) which have moved from a domestic monopoly to an actor within the global industry. Case examples are used to illustrate the internationalization processes of telcos from SMOPECs within the context of the whole industry value network. Chapter XII, “The Effect of Non-Market Strategies in the Mobile Industry” by Zulima Fernández and Belén Usero Sánchez, Universidad Carlos III de Madrid (Spain), analyzes the role of non-market actions (NMAs) in the competitive position of firms in the European mobile telecommunications industry. The findings of an empirical study confirming the effectiveness of legal actions as competition tools in the European mobile telecommunications industry are discussed. Chapter XIII, “Spatiality and Political Economy of the Global Fiber Optics Industry” by Barney Warf, University of Kansas (USA), reviews the historical development of this communications technology. The chapter discusses the spatial distribution of the world’s fiber lines, noting major transatlantic and transpacific markets and newer systems. Chapters XIV and XV “Digital Convergence and Home Network Services in Korea: Part 1 - Recent Progress and Policy Implications” and “Digital Convergence and Home Network Services in Korea: Part 2 – Business Models and Strategic Alliances” by Hyun-Soo Han, Hanyang University (South Korea); Heesang Lee, Sungkyunkwan University (South Korea); Yeong-Wha Sawng, Electronic and Telecommunica-

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tions Research Institute (South Korea), categorize three classes of typical services and five industrial participants with regard to Korea’s home network industry. These chapters investigate business interests of the industrial participants comprising convergent home network services, and explore the causes of conflicts among them. They discuss managerial implications and strategic alliance opportunities of the home network service providers in Korea. Strategic propositions for the success of the home network industry are suggested at the firm level with respect to three main converging home network services. Section III: Telecommunications Business Management consists of 15 chapters. Chapter XVI, “Mixing and Matching Organizational Network Legitimacy Practices to China’s Telecommunication Market” by Brian Low, University of Western Sydney (Australia); Wesley J. Johnston, Georgia State University (USA), presents a case research-based framework to describe an iterative and incremental process to help foreign telecommunications firms manage their network legitimacy. Chapter XVII, “Preliminary Knowledge Management Implementation in the Telco Industry” by Chin Wei Chong, Multimedia University (Malaysia); Siong Choy Chong, Putra International College (Malaysia), aims to create a unified model capturing and generalizing the different arrays of preliminary knowledge management (KM) implementation success factors in the telecommunication industry based on the studies in Malaysia. Chapter XVIII, “Activity-based Costing in the Portuguese Telecommunications Industry” by Maria Major, ISCTE – Business School (Portugal); Trevor Hopper, University of Manchester (UK), examines an implementation of an Activity-based Costing (ABC) system in a specific Portuguese telecommunications firm which provided international telecommunications services. The chapter explores how ABC was adopted and used to support decision-making and pricing strategies. Chapters XIX and XX, “The Role of Organizational Culture to the Management of Telecommunication Companies: I. Background and Motivation” and “The Role of Organizational Culture to the Management of Telecommunication Companies: II. Applications and Case Studies” by Antonios D. Kargas and Dimitris Varoutas, University of Athens (Greece), explain what organizational culture is and analyze its importance for the management. They present the theoretical link between organizational culture and a variety of variables, which affect organizational performance and efficiency. Chapter XXI, “Dynamics of Mobile Service Adoption” by Hannu Verkasalo, Helsinki University of Technology (Finland), discusses the adoption of mobile services. The study explores what drives the intention and actual use of some of the emerging mobile services, thus contributing to both industry and academic readers. Chapter XXII, “When Customer Satisfaction Isn’t Good Enough: The Role of Switching Incentives and Barriers Affecting Customer Behavior in Korean Mobile Communications Services” by Moon-Koo Kim, Electronics and Telecommunications Research Institute (South Korea); Myeong-Cheol Park, Information and Communications University (South Korea); Jong-Hyun Park, Electronics and Telecommunications Research Institute (South Korea), explains the relationship between customer satisfaction and customer behavior using switching incentives and switching barriers. Chapter XXIII, “Telecommunication Customer Demand Management” by Jiayin Qi, Beijing University of Posts and Telecommunications (China); Yajing Si, Beijing Wuzi University (China); Jing Tan and Yangming Zhang, Beijing University of Posts and Telecommunications (China), proposes a method that telecom operators can use to estimate their customer demand and respond to their demand automatically. Chapter XXIV, “Telecommunication Customer Detainment Management” by Jiayin Qi, Yuanquan Li, Chen Li, Yingying Zhang, and Jing Tan, Beijing University of Posts and Telecommunications (China), proposes an integrated methodological system of telecommunication customer detainment management which includes the customer churn prediction and customer detainment management. It discusses customer detainment management strategies. Chapter XXV, “How to Plan for an Upgrading Investment in a Data Network?” by Frédéric Morlot and Salah Eddine Elayoubi, Orange

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Labs (France), illustrates how a mobile data network operator can plan an upgrading investment to anticipate explosions of the demand, taking into account the expected profit and the customer satisfaction. The chapter then proposes and discusses two methods that help in making the decision: an actualization algorithm and a real option-like strategy. Chapter XXVI, “Telecommunication Investments Analysis: A Multi-Criteria Model” by Georgios Angelou and Anastasios Economides, University of Macedonia (Greece), deals with quantitative and qualitative analysis and integrates real options (ROs) and Analytic Hierarchy Process (AHP) into a common decision analysis framework providing a multi-criteria model for analyzing telecommunication investments in the deregulated business field. Chapter XXVII, “A Business Planning Framework for WiMAX Applications” by Rebecca De Coster, Brunel University (UK), introduces a business planning framework which identifies generic approaches for examining the market potential for WiMAX applications. Chapter XXVIII, “Adoption of VoIP Applications in Public and Private Organizations” by Nicoletta Corrocher, Bocconi University (Italy); Roberto Fontana, University of Pavia (Italy); Claudia Parlanti, Bocconi University (Italy), investigates the determinants of diffusion of VoIP applications in a sample of public and private organizations in Italy. Results suggest that organizations become more likely to adopt as time goes by, and that the decision to adopt is mostly affected by size and availability of financial resources. Chapter XXIX, “Intelligent Networking and Business Process Innovation: A Case Study Analysis of Home Box Office and Dell Computers” by Richard A. Gershon, Western Michigan University (USA), examines the subject of business process innovation which involves creating systems and methods for improving organizational performance. Special attention is given to the topic of intelligent networking which represents the combination of software, technology and electronic pathways that makes business process innovation possible for both large and small organizations alike. Chapter XXX, “Can M-commerce Benefit from Pervasive Computing?” by Stan Kurkovsky, Central Connecticut State University (USA), discusses a number of pervasive computing principles and illustrates how they have been implemented in mobile commerce applications. The chapter also presents new trends in developing context aware m-commerce services that tap into the power of Web 2.0 services and digital communities. Section IV: Telecommunications Technology Management consists of 12 chapters. Chapter XXXI, “Basics of Telecommunication Management” by Katalin Tarnay, University of Pannonia (Hungary), familiarizes the reader with the main components, functions, and key terms of telecommunications management. Starting at the definition of telecommunications management, it presents the management functions, the managed objects, the management information bases, and the main management protocols in a simple understandable way. Chapter XXXII, “Telecommunication Management Protocols” by Katalin Tarnay, University of Pannonia (Hungary), presents the reader with the fundamentals of communication protocols in telecommunications management. It presents the most widely used protocol, the Simple Network Management Protocol (SNMP), the open system management protocols, and the mobile internet management protocols for Authentication, Authorization and Accounting (AAA). Chapter XXXIII, “Cellular Network Planning- Evolution from 2G to 4G” by Marc St-Hilaire, Carleton University (Canada); Samuel Pierre, École Polytechnique de Montréal (Canada), presents the characteristics and the architecture of each generation of cellular networks (1G, 2G, 3G and 4G). Then, it exposes different planning problems related to each generation followed by a short description of different solutions that have been proposed in the literature. Chapter XXXIV, “IP Address Management: Challenges, Solutions and Future Perspectives” by Faouzi Kamoun, University of Dubai (UAE), discusses the most important challenges in IP Address Management (IPAM) and attempts to address some of the solutions and best practices to tackle these challenges. The chapter underlines the need for organizations to adopt proven



IPAM best practices. Chapter XXXV, “Digital Cable TV Networks: Convergent Technologies, Valueadded Services and Business Strategies” Ran Wei, University of South Carolina (USA) and Zizhong Zhao, Communication University of China (China), focuses on digital cable TV networks as a convergent network that provides broadcasting TV and radio, telecommunications services, and IP-based publishing and E-Commerce. This chapter examines the value chain and collaborative opportunities among the participants in the digital cable TV revolution. Chapter XXXVI, “Diffusion and Oscillation of Telecommunications Services: The Case of Web 2.0 Platforms” by Tobias Kollmann, Christoph Stöckmann, and Carsten Schröer, University of Duisburg-Essen, Campus Essen (Germany), focuses on the diffusion characteristics of Web 2.0 Platforms and provides management concepts for competition. The chapter shows that there is always a chance to capture a market or at least to grow against competition in a Web 2.0 setting. Chapter XXXVII, “The diffusion of WiMax Technology: Hurdles and Opportunities” by Phillip Olla, Madonna University (USA), discusses the potential of WiMax technology to deliver personal broadband and fixed Internet capabilities. The chapter applies components from the global diffusion of the Internet framework to analyze the current state of WiMax deployment. Chapter XXXVIII, “VoIP Quality and Security Issues for Consumers and Small Businesses” by David Bell, Pacific Union College (USA); Sunil Hazari, University of West Georgia (USA), reviews issues related to the quality and security of VoIP faced by consumers and small businesses. Chapter XXXIX “Emerging Security Issues in VANETS for E-Business” by S. S. Manvi, REVA Institute of technology and Management (India); M. S. Kakkasageri, Basaveshwar Engineering College (India), presents the emerging security issues in Vehicular Ad hoc Networks (VANETs) for E-Business, along with some of the solutions. Security issues discussed are authentication, trust, confidentiality, non-repudiation and detection of malicious users. Chapter XL, “Telecommunications Network Planning and Operations Management in an Academic Environment: The Case Study of the Aristotle University of Thessaloniki” by Sotirios K. Goudos, Angeliki Z. Agorogianni, and Zaharias D. Zaharis, Aristotle University of Thessaloniki (Greece), presents and discusses network management and planning issues in the Aristotle University of Thessaloniki, Greece. The network expansion and cost reduction case studies are discussed. It also discusses the migration analysis for future upgrades that will fully enable the use of emerging technologies such as Voice over IP (VoIP). Chapter XLI, “Planning of Wireless Community Networks” by Karoly Farkas, University of West Hungary (Hungary); Csaba A. Szabó and Zoltán Horváth, Budapest Univ. Tech&Econ (Hungary), discusses the applications, state-of-the-art technologies, planning methods, and business models for wireless community networks, and provides an integrated presentation of these essential parts with an ongoing digital city project in Hungary. Chapter XLII, “Human Factors for Business Mobile Systems” by David Golightly, University of Nottingham (UK), addresses human factors with particular relevance to developing and deploying business mobile systems. This chapter argues that it is critical to take an approach that puts users at the heart of a new technology or service development. This approach is presented as a three-stage model of context analysis, specification and design, and evaluation Section V: Telecommunications Technology and Applications consists of 11 chapters. Chapter XLIII, “Towards QoS-Inferred Internet” by Mohamed Boucadair, Pierre Levis, and Pierrick Morand, France Telecom-Orange Labs (France), focuses on two issues: provider-to-provider agreements and enhancements to inter-domain routing protocol to convey QoS-related information. Chapter XLIV, “The Playout Control Management: An Issue for the IP Telephony Service Providers” by Mirko Luca Lobina, Luigi Atzori, and Fabrizio Boi, Universita’ di Cagliari (Italy), proposes playout control management and planning strategies and compares the strategies IP Telephony Service Providers can choose with the aim of saving money and offering a better quality of service. Chapter XLV, “Open APIs and Protocols

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for Services and Applications in Telecoms” by Nikolaos D. Tselikas, National Technical University of Athens (Greece); Georgia M. Kapitsaki, National Technical University of Athens (Greece); Dimitrios G. Makris, University of Peloponnese (Greece); Iakovos S. Venieris, National Technical University of Athens (Greece), discusses the role of open APIs and protocols for advanced service provisioning. Specifically, the role and the trade-offs in modern telecoms between open APIs and Protocols, that is OSA/Parlay APIs, JAIN APIs and SIP, are discussed. Chapter XLVI, “On the Management Performance of Networked Environments Using Web Services Technologies” by Lisandro Zambenedetti Granville, Ricardo Neisse, Ricardo Lemos Vianna, and Tiago Fioreze, Federal University of Rio Grande do Sul (Brazil), provides a comparison between different strategies of integrating conventionally managed network devices into Web Services-based management processes. Chapter XLVII, “Automated Fault Management in Wireless Networks” by Raquel Barco and Pedro Lázaro, University of Málaga (Spain), proposes a system for automated fault management in the Radio Access Network (RAN). Some methods proposed for auto-diagnosis are also discussed. Chapter XLVIII, “Modeling Intrusion Detection with Self Similar Traffic in Enterprise Networks” by Cajetan M. Akujuobi and Nana K. Ampah, Prairie View A & M University (USA), proposes IDS technique, the novelty of which lies in its efficiency and ability to eliminate most limitations of existing IDSs and IPSs, thereby ensuring high-level network protection. Chapter XLIX, “High-speed Multimedia Networks: Critical Issues and Trends” by Dimitris Kanellopoulos, University of Patras (Greece), presents high-speed networking technologies and standards such as ATM, Fast Ethernet, 10 Gigabit Ethernet, SONET, RPR, PBT, PBB, T-MPLS and Optical Transport Network (OTN). It considers the requirements imposed to high-speed networks by multimedia applications and analyzes crucial issues of high-speed networking such as bandwidth problems, discarding policies and fast broadcast. Chapter L, “Emerging Telecommunications Technologies: Cognitive Radio” by J. Joaquín Escudero-Garzás and Ana García-Armada, University Carlos III de Madrid (Spain), introduces the novel concept of Cognitive Radio for wireless telecommunications. Cognitive radios are a new type of radio devices that include cognition and reconfigurability features. Chapter LI, “Game Theory for PHY layer and MAC sublayer in Wireless Telecommunications” by J. Joaquín Escudero-Garzás and Ana García-Armada, University Carlos III de Madrid (Spain), addresses the role of Game Theory for wireless communications. It introduces Game Theory and its fundamentals, and gives an overview of the applications of Game Theory in the wireless networks for PHY layer and MAC sublayer. Chapter LII, “Agent Based Product Negotiation Models in Mobile Commerce” by S. S. Manvi, REVA Institute of technology and Management (India); L. B. Bhajantri, Basaveshwar Engineering College (India), addresses various issues in m-commerce and presents various agent based product negotiation models in the mobile commerce environment. Chapter LIII, “Role of Telecommunications in Precision Agriculture” by James M. McKinion, USDA-ARS (USA), discusses the various data/information intensive precision agriculture applications which use wireless local area networking and Internet access, and the next generation technologies which can immensely propel precision agriculture to widespread use in agriculture. Section VI: Telecommunications Network Design consists of seven chapters. Chapter LIV, “Network Planning and Dimensioning for Broadband Access to the Internet Regarding Quality of Service Demands” by Franz Hartleb, Gerhard Hasslinger, and Sebastian Kempken, Universität Duisburg-Essen (Germany), focuses on planning and traffic engineering for link bandwidth and buffers as main resources in communication platforms based on measurement and statistical properties of traffic growth and variability. Chapter LV, “Overlay Networks: New Techniques for Global Service and Network Provisioning” by Gerhard Hasslinger, Deutsche-Telekom (Germany), discusses overlay networks within the standardiza-

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tion of Internet Protocols (IP), where the main focus is on evolving techniques on higher layers. Chapter LVI, “Optimising P2P Networks by Adaptive Overlay Construction” by Nick Antonopoulos and James Salter, University of Surrey (UK), proposes ROME, a layer which runs on top of the Chord DHT to provide control over network size through the monitoring of node workload and suggests the use of processes to control the addition or removal of nodes from the network. Chapter LVII, “Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier” by Susan J. Chinburg, Rogers State University (USA); George Scheets, Oklahoma State University (USA), expands the optimal network design process by applying a process borrowed from Finance and Operations Research/Management Science literature known as the Efficient Frontier or production frontier analysis. Chapter LVIII, “Combining Small and Large Scale Roaming Parameters to Optimize PCS Networks Design” by Mohamed Zaki and Salah Ramadan, Azhar University (Egypt), introduces a model that unites both an Enhanced Profile-Based Strategy (EPBS) for small-scale roaming and a Caching Two-Level Forwarding Pointer (C2LFP) strategy. The idea behind this model is applying those two location management strategies to specify the physical parameters of PCS networks from mobility management’s point of view. Chapter LIX, “Secure Resource Optimization in Distributed Service Computing” by Kaiqi Xiong, Texas A&M University Commerce (USA); Harry Perros, North Carolina State University (USA), presents a framework for optimizing a set of computer resources used by a service provider to host enterprise applications subject to a service level agreement (SLA). Chapter LX, “Trends, Optimization and Management of Optical Networks” by Jadranka Skorin-Kapov, Stony Brook University (USA); Darko Skorin-Kapov, Adelphi University (USA), provides a review of optical networking, its current issues, trends, and ways to efficiently design and manage a wide range of optical networks. The Handbook of Research on Telecommunications Planning and Management for Business is an excellent collection of the latest research and practices associated with emerging telecommunications policies, management, technologies, and applications. This book is the first comprehensive book that presents aspects from the government, industry, managerial, and technical sides of the telecommunications. As leading experts in the telecommunications area, the contributors did an excellent job of providing our readers with extensive coverage of the most important research topics, concepts, business practices, technologies, and trends in the telecommunications industry. The projected audience includes policymakers, telecommunications employees, managers, researchers, professors, and undergraduate/graduate students in various telecommunication management programs. I expect this book to shed new insights for researchers, educators, and practitioners to better understand the important issues and future trends of telecommunications research and technologies.

References Bauer, J.M. and Bohlin, E. (2008). From Static to Dynamic Regulation - Recent Developments in US Telecommunications Policy. Intereconomics, 43(1), pp. 38-50. Tallberg, M., Hämmäinen, H., Töyli, J., Kamppari, S., & Kivi, A. (2007). Impacts of handset bundling on mobile data usage: the case of Finland. Telecommunications Policy, 31(10/11), 648-659. Ubacht, J. (2004). Regulatory practice in telecommunications markets: how to grasp the ‘real world of public action’? Communications & Strategies, (54, 2nd Quarter), 219-242.

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Acknowledgment

I would like to acknowledge the help of the eighty-four expert reviewers involved in the double-blind review process for sixty chapters of the handbook, without whose support the book could not have been satisfactorily completed. I sincerely thank Ms. Kristin M. Klinger, Julia Mosemann, Heather A. Probst, Jan Travers, Mehdi Khosrow-Pour, and other members of the IGI Global, whose contributions throughout the whole process from the inception of the initial idea to the final publication have been invaluable. In closing, I would like to express my gratitude to the 111 authors for their invaluable contributions and collaboration. In Lee, Ph.D. Western Illinois University Macomb, IL, USA August 2008

Section I

Telecommunications Policy



Chapter I

Static and Dynamic Efficiency in the European Telecommunications Market:

The Role of Regulation on the Incentives to Invest and the Ladder of Investment Walter Distaso Imperial College London, UK Paolo Lupi AGCOM, Italy Fabio M. Manenti Università di Padova, Italy

Abstract In this chapter the authors provide evidence of the effectiveness of European National Regulatory Authorities in applying the basic principles of the ladder of investment. The analysis discusses and compares the regulatory approach adopted in 12 European Countries from January 2005 to July 2007. Results are not easy to interpret, given the peculiarities of the different national markets. Nevertheless, they can conclude that the policies adopted by National Regulatory Authorities are broadly consistent with the ladder of investment theory.

1. Introduction to the theory of investment ladder With the advent of next generation networks, the telecommunication sector is undergoing a deep

transformation: from an industry characterized by a “quasi-monopolistic” infrastructure to an industry where alternative networks compete with the incumbent (and with each other). It is widely accepted that these changes are actually challeng-

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Static and Dynamic Efficiency in the European Telecommunications Market

ing the regulatory approach towards telecommunications: while in the near past regulators’ efforts were aimed at introducing more competition into quasi-monopolistic markets, nowadays regulation also tries to create favourable conditions for the necessary capital investments needed to sustain and innovate the network infrastructure (see, among others, Bauer and Bohlin, 2008). This transformation also exacerbates the traditional trade-off between static and dynamic efficiency. Static efficiency occurs when marginal production costs are minimized (production efficiency) or when the price consumers pay in exchange of a good or service equals the production cost (allocative efficiency); on the other hand, dynamic efficiency relates to demand creation and innovation. While in competitive markets firms price at cost thus achieving static efficiency, competition may actually be the source of dynamic inefficiency since it reduces the incentives to innovate by preventing innovators from recovering the fixed costs of their investment in new technologies. Usually, industry regulators face this trade-off whenever they attempt to maximize static social welfare through price regulation, while providing firms with sufficient incentives to innovate (see, e.g., Guthrie, 2006). All these issues are particularly important in telecommunications, probably the most dynamic industry subject to sector specific regulation (for a theoretical and empirical analysis of the impact of regulation on the dynamic efficiency in telecommunications, see Prieger and Heil, 2008). Here, the tension between static and dynamic efficiency is so crucial that it is explicitly mentioned in the new European regulatory framework for electronic communications services. There, it is clearly stated that the scope of regulation is to “promote competition in the provision of electronic communications networks, electronic communications services and associated facilities” and to “encourage efficient investment in infrastructures and to promote innovation” (Framework Directive, Article 8.2.). 

Regulation may influence innovation in telecommunications either through prices or by impacting the dynamics of market entry (Bourreau and Dogan, 2001). In telecommunications, both retail and wholesale (interconnection) charges are heavily regulated. This has an impact on operators’ profits and, consequently, on their incentives to invest in innovative activities. At the same time, regulation may alter the terms of entry (which are often asymmetric, in the sense that entrant operators are often not subject to regulatory impositions) and, again, this is likely to have an impact on the degree of innovation undertaken by both the incumbents and entrant operators. In order to reconcile static with dynamic efficiency, European countries have implemented a set of common regulations based on the key regulatory instrument of local loop unbundling (LLU). LLU is the regulatory process whereby incumbent operators lease, wholly or in part, at a regulated price the local segment of their telecommunications network (usually pairs of copper wire) to competitors to let them provide voice and broadband services on the retail market. Regulatory provisions aimed at implementing LLU have been introduced in all member states since 2001. The regulatory framework adopted by the national regulatory authorities of all EU15 member states mandates incumbent operators the provision of a (more or less) wide portfolio of wholesale services that alternative operators aggregate according to their needs in order to provide voice and broadband services to their customers. More specifically, local loop unbundling usually comes in three forms: bitstream access, shared access and full local loop unbundling. Bitstream access occurs when the incumbent installs a high speed access link to the customers premises (e.g., by installing ADSL equipment in the local access network) and then makes it available to third parties. With bitstream access, entrants do not have control over the physical line nor are they allowed to add other equipment; therefore, entrants are

Static and Dynamic Efficiency in the European Telecommunications Market

restricted to resale the services designated by the incumbent operator (usually broadband internet access). Bitstream is a form of wholesale access usually chosen by less infrastructured alternative operators, whose proprietary network interconnects with the incumbent’s network through a limited number of higher-level points of interconnection. Alternatively, entrants may gain access via either shared access or full LLU. With shared access, the incumbent remains in control of the copper line and can still provide (voice) services to consumers, since entrants only lease part of the copper pair spectrum (the high-frequency, non voice spectrum). With fully unbundled access, the alternative operator obtains full control of the copper line and this allows him to offer both voice and data services. Shared access and, particularly, LLU are technically and economically viable only to operators with a sufficiently widespread network, able to reach most of the local exchanges of the incumbent. For this reason, they are usually the access option preferred by infrastructured operators. European countries have implemented LLU in order to favour entry by alternative operators and to reduce incumbents’ market power. Nevertheless, in line with the aforementioned tension between static and dynamic efficiency, many feared that wholesale access could undermine firms’ incentives to invest and to innovate. The argument goes as follows: LLU erodes incumbents’ profits and, consequently, their incentives to invest in new technologies and services. On top of that, by allowing entry without the need of a proprietary infrastructure, LLU would not provide incentives to invest by the entrant firms either. To solve this potential standstill, Martin Cave and Ingo Vogelsang have proposed a new approach to LLU regulation, known as the “ladder of investment” theory (see Cave and Vogelsang, 2003 and Cave, 2006). This theory is based on the idea that in telecommunications, initially essential facilities may become less essential over

time; this argument is not new in the literature (see, among others, Bourreau and Dogan, 2006),1 but the authors have reconsidered it to provide a novel approach to telecoms regulation. The mechanism underlying the ladder of investment is extremely simple. At the beginning, the regulator should encourage access to wholesale markets by setting very low access prices for the network elements that are too expensive for new entrants to replicate. As soon as new entrants consolidate their market position and have gained brand recognition and customer base, regulatory authorities should increase access prices, starting from the network elements that are easier to duplicate (i.e. bitstream access). The price increase of these network elements should encourage new entrants to invest on these elements, in order to migrate towards higher levels of the investment scale in infrastructure, i.e. to move up the “ladder of investment”. Ultimately, as soon as entrant operators have gained sufficient revenues and technological know-how, they can finally climb the last step of the ladder, i.e. they can invest in their own access infrastructure. In order for the investment ladder to work effectively and to induce operators to climb the ladder, national regulatory authorities should adopt what has been defined as an increased micro-management of access products (Cave, 2006), a carefully designed dynamic access regime. The ladder of investment theory has been extremely appealing to industry regulators and the European Commission since it offers a possible solution to the trade-off between static and dynamic efficiency; in fact, due to mandated LLU, entry and competition are guaranteed in the short run while operators are given the right incentives to invest (namely, to climb the ladder) through a dynamically appropriate design of access terms. The investment ladder has also some opponents, expressing doubts with regards to, at least, two aspects of the theory (see Oldale and Padilla, 2004). They argue that, on one side, it is doubtful



Static and Dynamic Efficiency in the European Telecommunications Market

that regulators are able to implement the required micro-management of access terms. Furthermore, it is not clear why LLU-oriented service-based competition should necessarily evolve into a robust facility-based competition. Finally, from an empirical point of view, the real efficacy of the theory of the ladder of investment has never been established.

2. Empirical analysis The aim of this section is to investigate empirically the ladder of investment theory. We start by surveying the most recent literature dealing with regulation and investment in telecommunications. As we will discuss briefly, the various empirical studies often reach different conclusions on the existence and the strength of the trade-off between static and dynamic efficiency in telecommunications. Furthermore, they often present various limitations and shortcomings that call for further investigations. In the second part of this section, we use a novel and detailed dataset on access lines and prices to check the validity of the investment ladder in various European countries.

2.1. Survey of Recent Studies The relationship between regulation and investments in telecommunications has been recently analyzed in a series of papers. Friederiszick et al. (2008) use firm-level data on tangible fixed assets as a measure of investment in telecommunications. Their sample is made of 180 firms in 25 European countries and the study covers the period 1996-2007. The use of a detailed data-set allows the authors to distinguish the effect of regulation between entrant and incumbent firms. Regulation is proxied by the Plaut’s regulatory index, which is explicitly constructed to account for the influence that a regulatory intervention may have on firms’ investment activities. The authors find no evidence of the investment ladder.



More specifically, they find that entry regulation discourages infrastructure investment by entrant firms in fixed-line telecommunications and does not significantly affect incumbents’ investment behavior. In other words, this study confirms the existence of the trade-off between static and dynamic efficiency highlighted in the theoretical literature. No evidence of the investment ladder theory is also found by two earlier papers, albeit not based on a systematic econometric analysis: Hausman and Sidak (2005), which focuses on the US, the UK, New Zealand, Canada and Germany, and Hazlett and Bazelon (2005), which concentrates on the US. A rather different result is reached by Jones and Salsas (2006), who present the outcome of a study commissioned by the European Commission’s DG Information Society aimed at identifying the main drivers of e-communications investments in the EU. As in the previous case, investment data are taken from annual reports of over 200 firms for the period 2001-04. For each country, the regulatory activity is proxied using the OECD regulatory index, which measures regulatory performance in terms of i) the degree of free entry into the market, ii) the extent of government ownership of the major operators and iii) market structure based on market shares. The index comes out to be significant, suggesting that those countries with lower performances in terms of regulatory activity (namely, less competition/entry and more government ownership of incumbent firms) are those that have less investment. On similar grounds, Cadman and Dineen (2006) investigate the relationship between regulation and investments in 9 European countries over 3 years. To measure the effectiveness of regulation in telecommunications, the authors use the ECTA scorecard, a composite index introduced by the European Competitive Telecommunications Association (ECTA). ECTA aggregated the responses submitted by national regulatory authorities and companies to a detailed questionnaire covering institutional framework and

Static and Dynamic Efficiency in the European Telecommunications Market

various market conditions (both competitive and regulatory conditions). The study finds a statistically significant relationship between regulatory effectiveness and investments, suggesting that in those countries where regulation supports market entry, a higher level of investments in telecommunications occurs. These studies reach different conclusions: in particular, the latter ones seem to contrast the traditional view, discussed previously, based on the existence of a trade-off between static efficiency and investment in fixed telecommunications. Nevertheless, all these results need to be taken cautiously for at least two important reasons: on the one side, these papers use investment data taken from companies’ annual reports. As discussed in OECD (2007): “The quality of data on investment by new entrants in telecommunication markets is poor. Definitional problems also exist in that the players in communication markets are no longer the traditional alternative operators providing voice services but a range of service providers including Internet Service Providers and cable television service providers who, through cable modems, provide VoIP services and broadband access”. This implies that investment data taken from annual reports can be a very poor indicator of operators’ real amount of investment in new technologies. Furthermore, they all use aggregated indices of regulatory effectiveness: these indices summarize various policy instruments and are often constructed in a very ad hoc way. As a result, it is rather questionable whether they effectively reflect the actual intensity of regulation in a given country (see Weeks and Williamson, 2006 for a series of arguments against the ECTA scorecards). A different approach is followed in Waverman et al. (2007), in a study conducted on behalf of the association of the European Telecommunications Network Operators (ETNO). The authors test the impact of specific aspects of access regulation embodied in the price of LLU on investment in alternative access platforms. Unlike previous

studies, this econometric model does not rely on indices or scorecards extrapolated in some way from market data and it does not use data on investments obtained from companies’ annual reports. Regulation is measured directly using data on LLU access prices while investments are proxied using growth rates in unbundled lines relative to facility-based lines, i.e. lines based on alternative infrastructures. The analysis goes from 2002 to 2006 and covers 27 European countries. The authors find evidence that lower local loop prices cause strong substitution from broadband offers over alternative platforms towards LLU-based broadband offerings and this substitution ultimately results in substantially lower investments in alternative access platforms. Interestingly, these findings move in a direction which is not compatible with that envisaged by the ladder of investment; although the authors are not completely critical of the concept of the ladder of investment, they make the reader aware of the risk associated with an improper implementation of this regulatory approach in Europe: as they suggest “the presumption of an enduring access bottleneck may tempt regulators into continuing to promote competition at lower rungs of the ladder (by offering access to incumbent networks on attractive terms) and thus result in a technologically stagnant marketplace.”

2.2. Results Similarly to Waverman et al. (2007), we test the ladder of investment theory by looking at the link between the prices of wholesale access services and the relative growth rates of the three alternative inputs that can be used by new entrants to provide access and broadband services to end users: bitstream services, LLU services and their own network. In other words, we overcome the difficulties associated with obtaining disaggregated data on investment in telecommunications infrastructures carried out by new entrants in each country, by proxying the level of this investment



Static and Dynamic Efficiency in the European Telecommunications Market

with the shares of the inputs used by new entrants to provide retail services. We track for each country the evolution of bitstream lines, unbundling lines and proprietary access infrastructures. If the ladder of investment is consistently applied, we might expect to see a migration from access services, like bitstream and resale, that require a low level of infrastructures – and therefore investment – to services, like shared access and LLU, that require an higher level of infrastructures and investment. We should also observe the share of LLU services to increase with respect to the share of bitstream services. Finally, and more importantly, we should expect an increase in the share of proprietary infrastructures, to reflect a move towards that kind of infrastructure. As discussed earlier, the Ladder of Investment (LoI) theory implies that National Regulatory Authorities (NRAs) follow a carefully designed dynamic access regime which, initially, requires to regulate the price of bitstream services at a very low level in order to promote service based entry. Once entry has occurred, NRAs should stimulate infrastructure investment (i.e. to climb the ladder) by a) increasing the price of bitstream services and b) decreasing the price of LLU services, a more infrastructured form of access. If the regulatory authorities follow a LoI regulatory approach, we should expect the ratio between LLU and bitstream access to decrease through time. Finally, in order to incentivize firms to develop proprietary networks, NRAs should progressively increase the price of LLU services. In order to graphically explore the relationship between investments and wholesale access prices, we show, for each country, two diagrams. The first is a so called “ternary diagram” plotting the evolution over time of the shares of the three inputs that, at an aggregate level, are used by new entrants to provide retail access and broadband services. The second is a plot of the ratio between the percentage changes (since



2005) in the regulated LLU price and the price of bitstream access. We use ternary diagrams because they allow to map in a two dimensional space the relative share of three variables – the three inputs – that sum up to a constant (one in our case). The share of each input is represented by the position of a point on an equilateral triangle.2 Each vertex of the triangle represents a distribution of inputs that puts all the weight on a single input, for instance the right vertex of Figure 1 represents a situation where firms use only ULL in order to provide retail access services. Points on the edges of the triangle represent situations where firms use only two of the inputs (the inputs that are on the two vertices connected by the edge), for instance points on the lower edge of the triangle in Figure 1 represent a situation where firms use a combination of bitstream and ULL services. Finally, points in the interior of the triangle represent a situation where firms use a combination of all three inputs. Of course, the closer one point to one vertex of the triangle, the higher the share of that input. In order to test whether NRAs use their regulatory instruments (the prices of mandated access services) according to the principles and the objectives of the ladder of investment, we have plotted the ratio between the percentage change in the price of an unbundled loop from the base year (2005) and the price of a retail ADSL line.3 We have proxied the price of a bitstream line with the price of the cheapest DSL offer of the incumbent operator because, given the complexities and peculiarities of the bitstream reference offers of European incumbent operators, it is almost impossible to derive for each country and for each time period a single representative price. We think that the price of a retail ADSL offer of the incumbent is a good proxy of the price of a bitstream line for several reasons. Firstly, during our period of investigation, almost all European NRAs were mandating bitstream prices based on the retail minus methodology that links the price

Static and Dynamic Efficiency in the European Telecommunications Market

of bitstream line to the price of a retail line. In addition, the value to be subtracted from the retail price, in order to get the wholesale bitstream price, is usually constant over time and does not differ significantly across countries. Lastly, in our case, we are more interested in variations in prices than in their absolute levels: variations in retail prices are immediately transmitted to bitstream prices through the retail minus methodology. If the LoI is in place we should expect that the dynamic path of inputs moves from a point close to the left vertex (area 1 in Figure 1) to a point close to the upper vertex (area 3 in Figure 1), passing through the right vertex (area 2 in Figure 1), thus indicating that entrants are effectively substituting resale and bitstream access with more infrastructured forms of access, that is they are “climbing the ladder”. On the other hand, if regulation is consistent with the investment ladder, NRAs should trigger the relative variation of the prices in order to incentivize new entrants to climb the ladder. Hence, in the price diagram we should observe a decrease in the ratio between LLU price variations and bitstream price variations. For our visual analysis of the investment ladder, we have combined data coming from different sources. All data on the number of resale, bit-

Figure 1. How to interpret ternary diagrams Own n e tw o rk

3

1

B itstre a m + re sa le

2

U LL + SA

stream, fully unbundled and shared access lines (as well as the number of DSL, CATV, broadband upgraded CATV, fibre optics and satellite lines) were taken from the “Broadband Access in the EU” reports that are published every six months by the Communication Committee of the European Commission. All data on the prices of fully unbundled loops were taken from the annual reports on the implementation of the telecommunications regulatory package of the European Commission.4 Data on retail prices for ADSL services of incumbent operators were taken from the Communication Outlook and the “Broadband Portal” of the OECD.5 For each country and each period we have chosen the price of the cheapest ADSL offer, with a download speed not lower than 640 Kbit/s, of the incumbent telephone operator. The dataset contains information for the following countries: Austria (AT), Belgium (BE), Denmark (DK), France (FR), Finland (FI), Germany (DE), Italy (IT), Netherlands (NL), Portugal (PT), Spain (ES), Sweden (SE) and United Kingdom (UK). We have half yearly observations from January 2005 to July 2007, the latest available figure. In order to better interpret and put into context the graphical information contained in the ternary and price plots, in Table 1 we also provide a measure of competition (denoted by Inc., the share of the incumbent operator in the broadband market), and a measure of penetration of the service (denoted by Pen., the ratio between the number of active broadband lines and the population). Our dataset starts in January 2005, when in most central European countries broadband services were already available since a few years; clearly at that time, the various countries were at different stages of the dynamic process implied by the ladder of investment. In other words, the starting point indicating the share of bitstream services, LLU services and own network used to provide access and broadband services by new entrants in January 2005 differed across countries. The fact that countries were at different stages (or



Static and Dynamic Efficiency in the European Telecommunications Market

Figure 2. Ternary and price plots AT

BE

DE

own network

own network

own network

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00   

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

  



 

00

00



 ULL + SA

. . Price ratio

.

0.

0.

.0

.

Price ratio

.0 0. 0.

0. 0. 00



bitstream + resale

.

. . . . .0

Price ratio

ULL + SA

.

bitstream + resale

.

ULL + SA

.

bitstream + resale

00

00

Year

00

00

00

Year

00

Year

DK

ES

FI

own network

own network

own network TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

     

 



TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

 

   

bitstream + resale

. Price ratio

. 00 Year

00

0.

0.

.0

.

Price ratio

.0 0. 0.

0. 0. 00

ULL + SA

.

.

. . . . .0

Price ratio

ULL + SA

.

bitstream + resale

.

ULL + SA

.

bitstream + resale

00

00 Year

00

00

00

00

Year

continued on following page





Static and Dynamic Efficiency in the European Telecommunications Market

Figure 2. continued FR

IT

own network

NL

own network

own network TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00



   

 

 ULL + SA

bitstream + resale

. Price ratio

. 00

00

0.

0.

.0

.

Price ratio

.0 0. 0.

0. 0. 00

ULL + SA

.

.

. . . . .0

Price ratio





bitstream + resale

.

ULL + SA

.

bitstream + resale

.



 

00

00

Year

00

00

00

Year

PT

SE

UK

own network

own network

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

00

Year

own network



TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

TIME  Jan00  Jul00  Jan00  Jul00  Jan00  Jul00

 



     

    

bitstream + resale

. Price ratio

. 00

00

Year

0.

0.

.0

.

Price ratio

.0 0. 0.

0. 0. 00

ULL + SA

.

.

. . . . .0

Price ratio

ULL + SA

.

bitstream + resale

.

ULL + SA

.

bitstream + resale



00

00 Year

00

00

00

00

Year

Figure : Ternary and price plots Our dataset starts in January 00, when in most central European countries broadband services were already available since a few years; clearly at that time, the various countries 



Static and Dynamic Efficiency in the European Telecommunications Market

different rungs) of the ladder of infrastructure puts us in a position to check whether the principles of the ladder of investment were implemented consistenly. Therefore, we first need to identify for each country where entrants were located on the investment ladder at the beginning of 2005. This distinction is crucial since, following the arguments proposed in Cave (2006), in order to make the ladder of investment operational, a NRA needs first to assess where on the ladder all firms are located to avoid a fundamental danger – namely that the ladder approach will slow down rather than speed up competitive investment. Following the input segmentation given previously, we can identify three types of countries: i) countries that in January 2005 fall in region 1 of Figure 1 (Type I countries), characterized by high adoption rates of resale and bistream services, and therefore by a low level of investments in LLU and own infrastructures. ii) Countries that in the same period fall in region 2 of Figure 1 (Type II countries), characterised by low levels of proprietary infrastructures but by a relatively large share of LLU and shared access services (at least when compared to Type I countries). iii) Countries that at the beginning of the sample

fall in region 3 of Figure 1 (Type III countries), characterised by the highest level of proprietary infrastructure. Once countries have been classified as type I, II or III, it is then possible to look at the evolution of the shares of the three inputs in the period January 2005-July 2007 and then to check whether in each country the regulatory approach implemented by the national regulator, represented by the price plots, is consistent with the dynamic access regime implied by the ladder of investment theory. From a simple inspection of the ternary diagrams it follows that Spain, France and Italy can be clasiffied as Type I countries. Germany and Finland, being characterized by a slightly higher level of infrastructured entrants, can be classified as Type II countries, while all remaining countries, having a rather large share of fully infrasructured entrants, can be classified as Type III countries.

Type I Countries (Spain, France and Italy) These countries are characterized by a very low level of access infrastructure which can be mainly ascribed to the absence (or the limited coverage)

Table 1. Broadband penetration and competition in selected EU countries (%) Country

10

Jan 2005

Jul 2005

Jan 2006

Jul 2006

Jan 2007

Jul 2007

Pen.

Inc.

Pen.

Inc.

Pen.

Inc.

Pen.

Inc.

Pen.

Inc.

Pen.

Inc.

AT

10

36.1

12

37.2

14.3

39.7

16.0

39.7

17.4

39.7

18.4

39.2

BE

16

49.6

17

48.8

19.3

48.3

20.8

48.4

22.4

47.8

23.9

46.8

DE

8

80.4

10

71.6

12.8

60.1

15.3

51.2

18.1

48.8

21.1

46.4

DK

18

58.2

22

55.4

24.7

58.7

29.7

59.7

31.4

63.2

37.2

63.7

ES

8

52.3

10

51.5

11.7

53.3

13.4

55.4

15.2

55.9

16.8

55.8

FI

15

72.3

19

66.8

22.4

66.4

25.0

66.5

27.1

69.7

28.8

69.1

FR

11

44.7

14

44.0

16.4

44.8

18.7

46.5

20.4

46.2

22.3

46.8

IT

8

73.1

10

70.8

11.8

71.7

13.2

67.9

14.5

66.6

15.9

64.8

NL

19

46.1

22

44.5

25.2

44.6

29.1

43.7

31.8

44.8

33.1

44.4

PT

8

80.7

10

79.1

11.6

76.3

12.9

72.1

13.9

71.1

14.8

70.1

SE

15

38.5

17

39.1

20.7

38.4

23.0

39.6

25.9

39.3

28.3

38.9

UK

10

25.1

14

24.8

16.5

24.8

19.4

24.3

21.7

25.2

23.8

25.7

Static and Dynamic Efficiency in the European Telecommunications Market

of cable TV networks. It is worth noting that Spain, France and Italy are, among all European countries, the ones where bitstream services have been available for a long time (since 1999). This is most likely due to the fact that there was no alternative platform to provide broadband services and therefore mandating access on the network of the incumbent was the only way to start a competitive dynamics in the country. In this scenario, the ladder of investment theory suggests to follow the dynamic regulatory access regime described previously, envisaged in a decreasing pattern of the ratio between the early price variation of an unbundled local loop and the price variation of a bitstream line. Price plots for France and, partially, Spain reveal that the national regulators have followed access regimes which are reasonably consistent with the investment ladder. The ternary plots seem to confirm the ladder of investment, since both countries have experienced a significant move towards a more infrastructured access: although in both countries the share of access through own network remains substantially constant over time, there has been a clear increase in the share of shared access and LLU. The Italian experience looks a little bit more controversial. In fact, despite a significant increase in the number of shared access and unbundled lines, as in Spain and France, the price plot reveals an access regime which goes in the opposite direction to the one suggested by a correct application of the ladder of investment. In this case, the more pronounced reduction of bistream prices relative to unbundling prices can be ascribed, at least to a certain degree, to the very high starting levels of bitstream prices. It may be worth noting that among Type I countries (see Table 1), France is the one that shows the highest level of competition and diffusion of broadband services. This result confirms the validity of the principles of the LoI, though it could be due, at least partially, to the more favourable initial position of France. In any case,

in 2005-2007 Italy shows the highest increase in competition, with a rise in new entrants’ market share of about 8.3%.

Type II Countries (Germany and Finland) In these countries, in January 2005 new entrants provided broadband access mainly through shared access and local loop unbundling, and very few access lines were offered through proprietary infrastructure. Despite having a similar wholesale structure at the beginning of 2005, Germany and Finland followed a completely different pattern in terms of both the evolution of access inputs and of policy adopted by the NRAs. Among the two countries, Germany is clearly the one that shows the most peculiar pattern. In fact (see the second and the third column of Table 1), Germany started from a market configuration in January 2005 characterised by a very low level of competition (the market share of the incumbent on the retail market was 80.4%) and by a very low level of penetration of broadband services. This situation is typical of countries where only some of the access products are initially available (at that time there was no mandated bitstream in Germany and a very low amount of resale lines), as market entry requires more initial investment by new entrants. In this context broadband penetration is usually very low, since the incumbent, not being challenged by entrants, inevitably tends to reduce its investment. We can therefore understand why the German NRA, worried by the disappointing state of the market, has descended the ladder by mandating bitstream services and ensuring the provision of higher levels of resale services. In this way Germany has sensibly increased broadband penetration and competition even if this latter form of competition, being mostly based on resale services, is by many considered to be less effective than competition based on other forms of inputs. 11

Static and Dynamic Efficiency in the European Telecommunications Market

Finland has followed a pattern that is compatible with the principles of the LoI. Looking at the ternary plots, the distribution among inputs has mainly remained constant over the 2005-07 period. This is perfectly consistent with the very limited relative variation of bitstream and unbundling prices. The relative stability of Finland both in terms of prices and inputs is confirmed by the stability of competitiveness and penetration: among the countries in our dataset, Finland’s ranking in those two measures remained almost unchanged between 2005 and 2007.

Type III Countries (Austria, Belgium, Denmark, the Netherlands, Portugal, Sweden and UK) The majority of countries in our dataset are Type III countries, where in January 2005 entrants were endowed with a significant amount of proprietary infrastructure. We can further classify these countries in two groups according to the dynamic patterns that emerge: countries that show no or limited variation in the distribution of inputs, like Belgium, Denmark and Netherlands, and countries that show a sensible variation in the distribution of inputs, like Austria, Portugal, Sweden and UK. The policies adopted by NRAs of both groups are compatible with the ladder of investment. Countries that belong to the first group are those that in January 2005 (see Table 1) showed the highest level of penetration of broadband services and where coverage of alternative networks, mainly cable TV, was the highest. In these countries, we could say that the mere existence of alternative infrastructures leads (more or less) automatically to competition and in fact Regulatory Agencies (see the price plots), have maintained access prices relatively unchanged. Countries that belong to the second group started in January 2005 from a lower level of penetration of broadband services. In these countries alternative cable networks had limited regional

12

coverage and influence (at least with respect to first group countries). As a consequence, also alternative operators’ ability to compete was limited. Therefore Regulators (see the downward sloping price plots), have used the access price instrument in a way compatible with the principles of the LoI. Recognising and acknowledging the difficulties in further expanding the penetration of services based on alternative infrastructures, they have favoured the development of the DSL part of the market – and the transition from bitstream to unbundling – that, in turn, stimulates competition with the cable segment of the market. We can therefore conclude that for these countries inter-platform competition is a result of the dynamics of infra-modal competition in the DSL segment of the market and not the cause of a competitive broadband market.

3. Conclusion In this paper/chapter we provide some evidence on the effectiveness of European NRAs in applying the basic principles of the ladder of investment. The results we get from our graphical analysis are not easy to interpret given the peculiarities of the different national markets, but we can conclude that the policies adopted by National Regulatory Agencies are in many, if not most, cases compatible with the ladder of investment. We are aware that having limited our analysis to the effects on the distribution of inputs induced by National Regulatory agencies’ price policies we have not fully covered the extent of the LoI principles. In fact, according to the LoI, Regulators have to support the upward move on the ladder either through dynamic pricing of the access wholesale services or through sunset clauses stating in advance that regulation will be removed and implying that new entrants should not establish themselves forever on a particular rung. However, at this stage, while most Regulators are still erecting the ladder, there are only a few

Static and Dynamic Efficiency in the European Telecommunications Market

regulators that are, at least on a geographic basis, removing bitstream regulations, and it is too early to anticipate when and in which way regulators will introduce the full set of LoI policies.

REFERENCES Bauer, J. M., & Bohlin, E. (2008). From Static to Dynamic Regulation - Recent Developments in US Telecommunications Policy. Intereconomics, 43(1), 38-50. Bourreau, M., & Dogan, P. (2001). Innovation and Regulation in the Telecommunications Industry. Telecommunications Policy, 25(3), 167-184. Bourreau, M., & Dogan, P. (2006). Build or Buy Strategies in the Local Loop. American Economic Review, Papers and Proceedings , 96(2), 72-76. Cadman, R., & Dineen, C. (2006). European Telecom’s Lost Investment: An analysis of the ECTA Scorecard. Strategy and Policy Consultants Network Ltd (SPC Network). Cave, M. (2006). Encouraging Infrastructure Competition through the Ladder of Investment. Telecommunications Policy, 30(3-4), 223-237. Cave, M., & Vogelsang, I. (2003). How Access Pricing and Entry Interact. Telecommunications Policy, 27, 717-727. Friederiszick, H., Grajek, M., & Röller, L. H. (2008). Analyzing the Relationship between Regulation and Investment in the Telecom Sector. Paper presented at International Industrial Organization Conference, Marymount University, Arlington, VA. Guthrie, G. (2006). Regulating Infrastructure: The Impact of Risk and Investment. Journal of Economic Literature, XLIV, 925-972. Jones, S., & Salsas, P. (2006). E-Communications: Investment and the Regulatory Framework. Communications & Strategies, 64, 29-39.

Hausman, J., & Sidak, G. (2005). Did Mandatory Unbundling Achieve its Purpose? Empirical Evidence From Five Countries. Journal of Competition Law and Economics, 1, 173–245. Hazlett, T. W., & Bazelon, C. (2005). Regulated Unbundling of Telecommunications Networks: A Stepping Stone to Facilities-Based Competition? Paper presented to the Telecommunications Policy Research Conference. OECD (2007). The Influence of Market Developments and Policies on Telecommunication Investment. DSTI/ICCP/CISP 6. Oldale, A., & Padilla, A. J. (2004). From State Monopoly to the “Investment Ladder”: Competition Policy and the NRF. In Swedish Competition Authority, The Pros and Cons of Antitrust in Deregulated Markets, 51-77. Prieger, J. E., & Heil, D. (2008). Is regulation a roadblock on the information highway? In I. Lee (Ed.), Handbook of Research on Telecommunications Planning and Management for Business. Hershey, PA: IGI Global (pp. 15-32). Waverman, et. al (2007). Access Regulation and Infrastructure Investment in the Telecommunications Sector: An Empirical Investigation. London Economics Consulting Group with the Support of ETNO, mimeo. September 2007. Weeks, M., & Williamson, B. (2006). A Sound Basis for Evidence Based Policy? A Critique of the ECTA Regulatory Scorecard and SPC Network Papers on Investment and Broadband. Paper prepared for ETNO by Indepen.

Key TERMS Bitstream Access: It occurs when the incumbent installs a high speed access link to the customer’s premises (e.g. by installing ADSL equipment in the local access network) and then

13

Static and Dynamic Efficiency in the European Telecommunications Market

makes it available to third parties. With bitstream access, entrants do not have control over the physical line nor are they allowed to add other equipment.

ENDNOTES

Dynamic Efficiency: It occurs when firms have an incentive to invest in innovation (either product or process innovation).

2

1



Full Local Loop Unbundling: The third party has total control over the local loop, in order to provide users both with voice and broadband services. 3

Local Loop Unbundling (LLU): The regulatory process of allowing multiple telecommunications operators the use of connections from the telephone exchange’s central office to the customer’s premises (the local loop). Ladder of Investment: A dynamic regulatory policy aimed at favouring access of existing network infrastructures in the first place, and then inducing entrants to invest in their own access networks (climb the ladder) through an appropriate micro-management of the access terms. Shared Access: The provision of access to the local loop by authorizing the use of the non-voice band frequency spectrum of the twisted metallic pair, whilst the local loop continues to be used by the incumbent to provide the telephone service to the public. Static Efficiency: It occurs when marginal production costs are minimized (production efficiency) or when the price consumers pay in exchange of a good or service equals the production cost (allocative efficiency).

14



The paper has been circulated as working paper since 2001. The equilateral triangle is the projection of the three-dimensional unit simplex onto the two dimensional Euclidean space. Each point’s coordinates are found by computing the gravity center of mass points using the data entries as weights. Thus, the coordinates of a point P(a,b,c), a+b+c=1, are: P(b+(c/2),c * sqrt(3)/2. In other words, all plots start at 1, then, for



year 2006, the plot shows



and, for year 2007, the plot shows

P06ULL P05ULL P06ADSL P05ADSL

P07ULL P05ULL , where pULL is the monthly P07ADSL P05ADSL



4





5

rental fee of an unbundled local loop and pADSL is the cheapest monthly fee of a broadband connection of the incumbent. The reports are freely available at http:// ec.europa.eu/information_society/policy/ ecomm/library/ communications_reports /annualreports/previousyears/index_en.htm. See http://www.oecd.org/sti/ict/broadband.

15

Chapter II

Is Regulation a Roadblock on the Information Highway? James E. Prieger Pepperdine University, USA Daniel Heil Pepperdine University, USA

Abstract Regulatory policy in telecommunications must balance short-term efficiency (low prices) against the firms’ incentives to innovate, which have longer reaching impacts on economic welfare. Historically, policy tended to sacrifice dynamic efficiency for the sake of competitive prices and static efficiency. In the last few decades, economists and other researchers have begun to document the large welfare costs of ignoring dynamic efficiency. We analyze the theoretical impact regulation has on innovation. We then turn to the empirical evidence that regulation dampens firms’ incentive to innovate in the telecommunications industry in general and the market for broadband Internet access in particular. Both product and process (cost reducing) innovation are discussed. The chapter forms a compendium of available research on the intersection of telecommunications regulation and innovation. We conclude with lessons the literature provides to policy makers and a discussion of future regulatory trends.

Introduction For much of the 20th century, regulatory policy directed toward the telecommunications market was concerned with “getting the prices right”. Regulators took the set of existing firms and products as given and sought prices that maximized consumer

surplus, subject to the constraint that the regulated firm cover its costs of providing the current set of services. Although other regulatory objectives such as universal service played a role, regulation was framed within an essentially static view of the market. In the latter part of the century, however, as the pace of technological change increased in

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Is Regulation a Roadblock on the Information Highway?

the telecommunications industry, it became clear that regulation could hinder innovation. In this chapter, we consider the evidence that regulation dampens firms’ incentive to innovate. We begin by laying out the theoretical reasons underpinning this notion. In the main section of the chapter, we review the empirical studies in the literature, focusing on the U.S. market. In so doing, we find remarkably consistent evidence from numerous institutional and geographic settings that lighter forms of regulation encourage innovation. Before proceeding, we must ask what innovation is. The term is used in the economics literature to refer to everything from basic invention to new product introduction to diffusion of existing technology. We use the term in a broad sense to refer to the making available of something new in a given market. It is useful, however, to distinguish between process and product innovation. Process innovations are advancements in the methods of creating existing products, and may not be directly apparent to consumers. Process innovation lowers the cost of producing goods or services currently available to consumers. Product innovation is the creation (or diffusion to new markets, in our expansive definition) of new goods previously unavailable to consumers. Regulation affects firms in many ways. Regulators historically deemed regulation justifiable, to reap the economies of scale and scope created by a single service provider and to further social goals such as universal service, while avoiding the inefficiency due to monopoly pricing. Regulatory control over prices and profits was chosen instead of reliance on competition or antitrust policy, which is generally not designed to prevent market expansion by firms with legitimate cost advantages over rivals. Competition law, at least in the U.S., furthermore does not outlaw the unilateral exercise of market power in setting prices. The economic inefficiency created by prices above their competitive level is illustrated in Figure 1, which depicts the demand and marginal cost curves for a telecommunications service. Total

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economic benefits from the service are the entire area between the demand and the marginal cost curves. Benefits are maximized when quantity Q* is provided (as would happen if the competitive price P* is charged). These social benefits, shared between the consumers and the firm, arise because one part of society (consumers) consumes units for which it is willing to pay more than it costs another part of society (the firm) to produce. If a carrier with some market power charges a higher price, such as Pm, then a lower quantity Qm of the service is purchased and the market loses benefits in the amount of area DWL in Figure 1. This deadweight loss, also known as the “Harberger triangle”, represents the dollar value of the economic benefits lost to consumers and the firm from units between Qm and Q* that are not consumed at the higher price. Deadweight loss is a static loss in welfare, because it is calculated given the service is already available. The Harberger triangle is not the end of the story, because a regulatory regime that attempts to squeeze static inefficiency out of market prices may create dynamic inefficiency. Dynamic efficiency stems from the additional net surplus created by new products and services. In Figure 1, the surplus obtained by consumers each period from the existence of the service is triangle CS, sometimes called the “Dupuit triangle”.1 The firm gains producer surplus, the unshaded area PS. If regulated prices are too low to encourage inFigure 1. Static versus dynamic efficiency

Is Regulation a Roadblock on the Information Highway?

novation, so that the product is never introduced, then consumers and producers miss both benefits (although the firm saves the cost of innovating). Thus, as Bourreau and Doğan (2001) and many other authors point out, regulatory policy is a balancing act that often trades increased static efficiency for decreased dynamic efficiency. The focus of this chapter, the dynamic costs of regulation, has received much less attention than have the static effects (Joskow & Rose, 1989). In the next section, we analyze the impact regulation has on innovation by means of a simple model (the details of which are in the appendix). We then turn to the empirical evidence on the interplay between regulation and innovation in the telecommunications industry in general, and the market for broadband Internet access in particular. In these sections, we include every relevant formal econometric study pertaining to the U.S. case that we could find, as well as representative studies using data from other countries or international comparisons.2 Thus, the meat of this chapter—and our main objective—is a compendium of the available research on how innovation depends on regulation in the telecommunications industry.3 We conclude with lessons the literature provides to policy makers and a discussion of future regulatory trends.

How does regulation affect innovation? The likely impact of a market intervention can be analyzed by studying how the regulation changes firms’ incentives. While some regulatory schemes such as price caps are known as “incentive regulation” in particular, it is important to realize that any regulation, if it affects the actions of the market participants at all, does so by changing their incentives. The economic study of regulation thus entails looking at how regulation changes the profit function of the firm. When the profit function changes, the actions the firm

takes to maximize profit also change. Take the case of product innovation. Regulation can affect firm’s incentives to product innovate through three channels. There are direct effects through mandates, indirect effects stemming from changes in the cost of bringing a new product to market, and indirect effects stemming from changes in operating profits gained by new products. Most visible are the direct effects of regulation on innovation. For example, a line of business restriction placed on the U.S. Bell Operating Companies (BOCs) after the breakup of the AT&T Bell System in 1984 prevented the BOCs from manufacturing telecommunications equipment. The incentive to introduce a new manufactured product, therefore, was dwarfed by the cost to the firm of the legal difficulties that would have ensued. Other examples of direct impacts of regulation include social contracts between the regulator and the firm, which are often the outcome of a public utility commission’s review of a merger case or renewal of a regulatory regime. In such contracts with the regulator, the firms often commit to putting new services on the market or making existing services available in more service areas. The merger of Ameritech and SBC in 1999 provides an example of the latter. Ameritech, the incumbent local exchange carrier (ILEC) in five Middle Western states, had (in the eyes of the federal and state regulators) dragged its feet in making digital subscriber line (DSL) services available to customers. Before approving the merger, the Federal Communications Commission (FCC) extracted commitments from the companies to promote advanced services such as broadband Internet access. In particular, SBC was required to locate at least 10% of their advanced service facilities in low-income areas. The requirement had teeth: penalty payments of more than $2 billion were specified. Subsequent to the merger, SBC deployed DSL more rapidly in the area (Hu & Prieger, 2008).

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Is Regulation a Roadblock on the Information Highway?

In contrast to the obvious effect that direct regulatory prohibitions and deployment mandates have on product introduction, many (indeed, most) effects of regulatory policy are indirect. To see how, we introduce a simple model of the firm’s decision problem, the details of which are in the appendix.4 Any innovative firm has many potential ideas for new goods that it can develop and offer. Some projects would provide higher operating profit if implemented, others lower. The firm will introduce new goods only if they have operating profits in excess of innovation cost (which includes everything from basic research through development and product launch costs). The number of new goods passing the profitability threshold each period determines the rate of innovation. We can now use this framework to consider some indirect impacts of regulation on innovation. The first type of indirect regulatory effect is on the cost side. Regulations that affect the cost of innovation include mandated regulatory filings and hearings before a public utility commission before introducing a new service. Cost studies that a firm must perform before a state commission approves rates for a new service are an example of the indirect costs of regulation. Hearings and cases in the legal and regulatory arena can also be expensive for the firm. For example, before (and even after) the BOCs could introduce information services there was a drawn-out string of federal court cases stretching from the late 1980’s into the mid 1990’s (Prieger, 2002).5 Such regulatory costs increase the cost of innovation. In response, some projects that were barely profitable before are lost—never brought to market—because of the increase in regulatory costs. However, highly profitable projects (which are typically so because they provide sizable benefits to consumers) are still pursued. Unless the additional costs created by regulation are large, or there any many potential projects that are minimally profitable before the cost increase, the number of new products lost because of these cost effects of regulation may be minimal. 18

The second type of indirect regulatory effect is on the benefit side. Regulations that effectively increase the time to market of a new product reduce the present value of the project by delaying the accrual of service revenue. Examples from telephone regulation abound. Many states and the FCC traditionally required hearings or minimum approval delays of tariffs for new services, designed to protect consumers from the “deleterious consequences of innovation,” as one regulatory official put it (Oppenheim, 1991). The studies by Prieger (2001, 2002) cover examples from state and federal jurisdiction. Regulation can also limit revenue from a new product through other means. One avenue is through competition. Under the unbundling regime instituted by the Telecommunications Act of 1996 in the U.S., incumbent telecommunications carriers must unbundle and lease to rivals certain parts of their network. The return on deploying the infrastructure is risky, and the carrier cannot fully recover the cost of investment after it is sunk. Thus, unbundling creates an asymmetry between incumbents (which bear the risk) and competitors (which, because they can stop renting at any time, do not). Renting unbundled network elements (UNEs) thus grants competitors a “free option”, and the extra competition reduces the return on the incumbent’s investment.6 Gayle and Weisman (2007) note that while unbundling may readily increase competition in telecommunications, the increase comes at the expense of investment that is vital for future innovation. Regulation can affect the competitive environment and the benefits a firm expects from introducing new products in other ways, as well. Regulatory policy can encourage competition through means other than mandating resale and unbundling, such as by requiring interconnection between competing networks. Regulation can also create legal monopoly (e.g., the Bell System in the U.S. until 1984), which enhances the incumbent’s ability to appropriate the social benefit created by innovation. Monopolies, however, may cannibal-

Is Regulation a Roadblock on the Information Highway?

ize demand for one of their existing products by introducing a new one, which increases the opportunity cost of innovation (Arrow, 1962). Other features of the general regulatory regime a carrier operates under can reduce the benefits from innovation. For example, “prudency reviews” were a common feature of rate of return regulation (RORR), the most common form of utility regulation in the U.S. for much of the 20th century (Kolbe & Tye, 1990). If the regulator deemed a failed investment to be imprudent, it would be stricken from the rate base upon which the firm’s allowed rate of return was calculated, reducing the firm’s revenue. RORR also attenuates incentives for process innovation, since excess returns gained thereby last only until the next regulatory review (Cabral & Riordan, 1989).7 Alternative regulation, which includes price caps, earnings sharing plans, rate freezes, and other schemes may provide greater incentives for innovation. We discuss alternative forms of regulation more in the next section. For example, tariffs for new services require no cost studies or prior approval under the FCC’s price cap regulation. Also, under price caps a dollar saved on cost (through process innovation) is retained by the firm, in contrast to RORR. However, even under alternative regulation the present value of the anticipated revenue from a new product is typically lessened, unless the regulation has no impact on the firm’s activity at all. When regulation reduces the revenues expected to follow from new products, fewer projects will pass the profitability threshold. Thus, similar to the case in which regulation increases the cost of innovation, when regulation limits revenue fewer new goods are introduced and the innovation rate drops. In contrast to the usual view that regulation sacrifices dynamic efficiency on the altar of static efficiency, proponents of regulation sometimes claim that regulation encourages innovation. In the context of our simple framework, this could happen only if regulation lowered costs or in-

creased revenue. It is difficult but not impossible to imagine cases where regulation accomplishes such changes. One oft-cited role for the regulator is to set technological standards in markets such as mobile telephony where coordination among firms, perhaps due to network effects in demand, is important. A standard imposed by the regulator that speeds consumer acceptance of a product can therefore increase revenue (or lower the cost of coordination). However, for every example of successful regulatory standard setting (e.g., perhaps, the GSM standard for European mobile telephony), one can find examples of failure. For example, the FCC’s delayed approval of a standard and spectrum allocation rules for mobile telephony for about 14 years during the nascence of the industry in the U.S. Furthermore, industry-led efforts to coordinate are often successful absent regulatory intervention (e.g., the International Telecommunications Union (ITU) standards for Group 3 fax transmission). Regulatory rules affecting competition, similarly, can also have conflicting effects on the rate of innovation. Increasing incentives for entrants to bring new services to market may diminish incentives for incumbents to do the same, and the net effect on innovation is ultimately an empirical matter in each market studied. We take up the empirical evidence in the next section.

Empirical evidence Economic theory thus suggests that regulation may hamper innovation, at least by incumbents, but theory alone cannot accurately measure the impact in any given market. The numerous regulatory reforms in the U.S. telecommunications industry over the past few decades give researchers a unique opportunity to quantify the consequences of various types of regulation. Compared to the vast number of papers related to the static effects of various regulatory schemes, there has been only limited effort directed toward quantifying

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the impact of regulation on innovation. Joskow and Rose (1989) find this “distressing” given that the “static gains and losses from regulation are probably small compared to the historical gains in welfare resulting from innovation and productivity growth.” Nevertheless, some researchers have compared the amount of innovation under the traditional RORR and incentive regulation. In the following section, we outline the empirical findings concerning the amount of innovation under divergent regulatory schemes. We also examine attempts to quantify the effects of regulatory delay on innovation. In addition, we review empirical findings on how unbundled network elements (UNEs) affect innovation. Finally, we explore endeavors to measure the value of the loss to society from the postponement of product introductions due to regulation. Process and product innovation are covered in separate subsections, and a final subsection reviews the literature on the broadband Internet access market as an indepth case study. Before delving into the empirical literature, it is important to point out several possible pitfalls for researcher. Kridel, Sappington, and Weisman (1996) discuss the problems posed by demonstration effects, sequencing effects, and before-and-after study designs. The demonstration effect pitfall occurs when regulated firms, in an attempt to encourage favorable regulatory reforms, artificially “demonstrate” the success of these regulations. Thus, any positive action a firm takes after regulatory reform may not result from better incentives to innovate. On the contrary, the actions of the firm may merely be a strategic (and temporary) decision to encourage permanent regulatory changes that are favorable to the firm. If the demonstration effect is substantial, then the positive effects of incentive regulation that many researchers find may persist only in the short term. A related hazard is the sequencing pitfall, in which firms hold off investment or innovation

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until the anticipated introduction of more favorable regulations. If the sequencing pitfall occurs, then innovations attributed to newly adopted regulations may also reflect only a short-term change in the firm’s behavior. A third pitfall occurs with before-and-after empirical models (Sappington & Weisman, 1996), in which performance in a period before the new regulation is contrasted with a period after. Since regulatory change is not conducted under conditions of a controlled experiment, such models can confuse the effects of regulation with trends in innovation that are exogenous to the regulatory reform. With these potential pitfalls in mind, we can review the conclusions found in the empirical literature.

Process Innovation Process innovation occurs when a firm, operating efficiently given its current technology, lowers its operating costs further by implementing new technology. Hence, researchers, when examining process innovation, often focus on changes in a firm’s costs.8 Stimulating process innovation is often a goal of regulatory reform. For example, one of the intentions behind the transition from RORR to incentive regulation was to provide firms with better incentives to reduce costs and deploy digital infrastructure. The empirical literature concerning regulation’s impact on firms’ performance categorizes regulatory regimes differently, although generally a distinction is made between traditional RORR and alternatives. Ai and Sappington (2002) provide a good example of regulatory classification. They distinguish between RORR and three types of incentive regulations: rate case moratoria, earnings sharing regulations, and price cap regulations. Earnings sharing regulations give the firms greater control over which rates and services to offer, but require firms to return to consumers a percentage of their earnings above certain thresholds. Under most earnings sharing regulations, the firm is prohibited from increas-

Is Regulation a Roadblock on the Information Highway?

ing its earnings above a certain point. Firms with mandated earnings sharing will thus not have an incentive to lower costs beyond a certain level. Earnings sharing regulation is thus similar to RORR, in that both regulatory schemes focus on the profit being made by the firm rather than the prices of the services in question. Rate case moratoria are typically an intermediate regulatory scheme in which regulated firms are freed from traditional RORR and given greater control over setting rates. Under price cap regulation, there are no direct constraints on profit and the firm instead faces a limit on how high it can raise its prices. Greenstein, McMaster, and Spiller (1995) note that firms under most price-cap regulations have greater control over prices than have firms regulated by traditional profit regulation like RORR. Kridel et al. (1996) review a variety of earlier papers related to incentive regulation and find mixed evidence concerning reductions in operating costs.9 Ai and Sappington (2002) perform a careful study and test empirically whether the introduction of incentive regulation did in fact lower the cost of producing existing services. They observe that rate case moratoria do indeed lower production costs compared to RORR in their sample of ILECs in the period 1986-1999. Surprisingly, other forms of incentive regulation do not produce significantly lower production costs than RORR, holding all else constant. The authors suggest that this finding may be due to the regulated firms’ fear that lower production costs will cause regulators to “ratchet” the standards for the firm’s performance upwards, thereby making any gains temporary. When local competition is present, regulation does indeed reduce production costs relative to RORR. This finding supports the notion that incentive regulation should be complemented by increased competition to realize the theorized gains of incentive regulation. The deployment of digital infrastructure under various regulatory schemes is an important aspect of process innovation since it lowers the

cost of providing services. Moreover, increases in digital infrastructure enable new services that require greater digital capacity. Ai and Sappington (2002), Greenstein et al. (1995), Tardiff and Taylor (1993), and Taylor, Zarkadas, and Zona (1992) find that incentive regulation leads to increased deployment of digital infrastructure, such as fiber optic cables and digital switches, when compared to RORR. Greenstein et al. (1995) conclude that if all states had adopted some form of pricing regulation ILECs would have installed at least 75 percent more fiber optic cables than under the status quo. They do not, however, find evidence that earnings sharing would have produced results drastically dissimilar to those under RORR. Ai and Sappington (2002), in contrast, find that deployment of digital infrastructure is more extensive under all types of incentive regulation—including earnings sharing—than under RORR. Unlike the other studies, Ai and Sappington (2002) correct for the endogeneity of the regulatory regimes10 in their econometric modeling, and thus have the strongest claim to finding true causal effects of regulation. They also find that the amount of digital infrastructure added to a local area under earnings sharing regulation increases when local competition increases. To sum up the literature on process innovation: incentive regulation appears to spur the deployment of next-generation infrastructure, and perhaps to lower operating costs. The latter result does not always hold empirically, in contrast to the predictions from theory. The divergence may be explained by the fact that regulators in practice are often not able to commit to adhering to the incentive regulation when the temptation to return excess profit to consumers arises. If firms look forward to only short term gains from reducing costs, then their incentive to process innovate is blunted.

Product Innovation Despite the limited amount of research on regulation and process innovation, until recently there 21

Is Regulation a Roadblock on the Information Highway?

has been more work looking at process innovation than at product innovation. Given the difficulty of counting innovations not created due to regulation, the imbalance is not surprising. Recent years have witnessed more attempts to quantify differences in product innovation under varying regulatory schemes, but the literature is still sparse. In addition to the usual comparison between RORR and incentive regulation, questions of regulatory delay become especially important when examining product innovation. Regulatory delay occurs when regulators prevent new products from entering the market until significant regulatory review has occurred. Regulatory delay may enhance social welfare by ensuring that new products meet certain guidelines, but may also create a disincentive for firms to release new services. In an early attempt to study product innovation in the telecommunications industry, Mueller (1993) examined the effects of extreme deregulation. In 1987, while other states were adopting earnings sharing or price-cap regulation, lawmakers in Nebraska opted to remove nearly all restrictions on the telecommunications industry. Firms were allowed to introduce new products and change rates with little regulatory oversight. Of 100 new services offered by U.S. West that Mueller (1993) randomly selects for the study, 37 were first introduced in Nebraska. The result of Nebraska’s experiment supports the contention that deregulation spurs firms to create new services. However, U.S. West likely opted to release new services in Nebraska first in order to demonstrate the benefits of such extreme deregulation. This is an example of the demonstration effects pitfall (Kridel et al., 1996), and it likely explains a portion of the increase in new services in Nebraska. Mueller’s findings may have limited validity in other settings, especially since no formal econometric model is used in measuring the impact of extreme deregulation. More recent attempts to quantify the amount of product innovation under various regulatory schemes have used more formal econometric

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models. Regulators in Indiana replaced traditional RORR with a mixture of incentive regulation and deregulation. Firms were allowed to set prices and the long regulatory delays witnessed under RORR were significantly reduced. Prieger (2001) estimates that the dominant ILEC (Ameritech) created new services 2 to 4.5 times faster than it did under the previous regime. Moreover, Ameritech, would have introduced up to twelve times as many services had reform been enacted at the beginning of the observed period. The author cautions, however, that the model consists of only two periods, one before introduction of the new regulations and one after introduction, with no “control” state. Thus the pitfall cited by Sappington and Weisman (1995), in which trends in overall innovation rates are indistinguishable from the actual regulatory effects, cannot be avoided. Prieger (2004) confronts the problem posed by before-and-after study designs by using unique data covering three periods of regulation for information services offered by dominant ILECs. The first and third period had extensive FCC regulation that created significant regulatory delay and forced firms to file extensive paper work before the approval of new services. The second, interim period had lighter regulation. The empirical evidence shows that firms introduced considerably more new services during the interim than during the first or third periods. In fact, the model predicts that the rate of product innovation was anywhere from 60% to 99% higher during the interim. Furthermore, these new services reached consumers much quicker during the interim since firms did not face any significant regulatory delays. The author’s data and study design minimizes the potential for the before-and-after problem, but the sequencing pitfall remains a possible problem. If firms withheld innovations near the end of the first period in order to release them during the more profitable interim, then the significant increase in new services during the interim is not the result of better incentives to innovate under less regulation. The author addresses the sequencing

Is Regulation a Roadblock on the Information Highway?

pitfall and ultimately concludes that it does not significantly affect the results. Prieger (2007) presents a theoretical model that predicts that a reduction in average regulatory delay would result in introduction of new services more quickly. These theoretical predictions are tested empirically by examining the number of new services offered in four states that adopted reforms designed to significantly reduce regulatory delay. The evidence confirms that the theoretical prediction: shorter regulatory delays lead to quicker product innovation. Thus, Mueller (1993) and Prieger (2001,2004,2007) all consistently find that lighter regulation does indeed encourage greater product innovation. Increases in social welfare due to the creation of new products is an important aspect of the study of regulation and product innovation. While it is unrealistic to expect a precise measurement of the gains and losses to society caused by telecommunications regulation,11 some attempts have been made to determine the welfare losses or gains from certain regulations. Hausman (1997) examines regulatory delay by the FCC in approving the widespread availability of cellular telephones. He finds that the loss to consumer welfare in 1983 from regulatory delay was somewhere between $16.7 and $24.3 billion in 1983 dollars. Total losses were much higher, given that mobile telephony could have been introduced a decade earlier than it was in the U.S. In similar fashion, Hausman (1997) estimates that regulation preventing AT&T (before divestiture) and the BOCs (after) from offering voice mail services cost consumers $1.2 billion per year. Prieger (2004), who examines the regulatory regime (CEI) put into place once the BOCs were allowed to offer information services, uses Hausman’s (1997) calculations to estimate the effect of regulatory delay on voice mail services. The potential cost to consumers in delayed availability of voice mail services due to the CEI regime ranges from $690 to $910 million. Prieger (2004) notes that voice mail is merely one of dozens of

information services delayed by regulatory action. However, Hausman’s figures for voice mail cannot be extrapolated to other services, because many of the others were much less subscribed than voice mail services. Moreover, some of the services held up by regulatory delay were substitutes for a service already available. The introduction of such services would probably increase consumer surplus far less than would truly novel services. We have not found other attempts to quantify the loss in consumer welfare caused by regulation.

A Case Study of the Broadband Internet Access Market We turn now to one specific sector of the telecommunications industry: the market for broadband Internet access. The spread of Internet access— first narrowband, and now broadband—is one of the most studied phenomena in the literature on regulation of telecommunications. As in the rest of the chapter, we focus mainly on the U.S., but also draw international studies into the discussion at times. Growth in broadband Internet access (hereafter, “broadband” for short) has been rapid in the U.S., especially compared to the spread of other recent services such as mobile telephony (Faulhaber, 2002). The growing importance of broadband in the national economy is large but difficult to quantify. The benefits of broadband that accrue to consumers are worth hundreds of billions of dollars per year in the U.S. (Crandall & Jackson, 2003). Total benefits are even higher, since business’ profits are not included in the estimate. Such rapid growth raises questions related to policy. Did good regulatory policy in the U.S. encourage the spread of broadband? Or, as some claim (e.g., Hausman, 2002), could broadband have diffused even faster in the U.S. (as it did in other countries such as Japan and Korea) if regulatory roadblocks had been removed? In this section, we look at the evidence available. As in other segments of the telecommunications industry in the U.S., regulatory policy toward

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broadband is a welter of partly coordinated (at best) state and federal efforts.12 State level direct subsidies for broadband are relatively rare: one survey found that only three states targeted tax incentives toward broadband deployment in 2001 (Lee, 2001). However, not all states were included in the survey, and a later study found 15 states with broadband tax incentives (Wallsten, 2005). Wallsten (2005) estimates the impact of other state policies directed at broadband, including private-sector grants and loans targeted to deployment in underserved or rural areas and use of universal service mechanisms to stimulate investment. None of these is positively correlated with the per capita broadband rate in the state,13 except for rural-targeted grants, and some even have negative correlation. Federal subsidies for carriers are not available for broadband specifically, although rural and high-cost areas receive general support for infrastructure, some of which may enable advanced services. Federal demand-side subsidies include the “e-rate” for schools and libraries. Although billions have been spent on the subsidies, Flamm (2005) finds no measurable effect on broadband availability. In sum, while it is not hard to find case studies of this or that neighborhood, organization, or school that benefited from being brought online by a subsidy program, there is scant evidence that the state and federal money spent has had large enough impacts to be measurable by econometric studies. Some of the programs are relatively recent, however, and the conclusion may change as time elapses and more data become available. Lee (2001) reports that at least 14 public utility commissions hold rate hearings for broadband rates, but Wallsten (2005) states that nowhere do states set rates for broadband, a discrepancy not easily reconciled. There is no federal rate regulation. In any event, we know of no study examining whether direct rate regulation of broadband affected its deployment by providers or take-up among consumers.

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The likeliest places to look for the impact of state policy on broadband are the general regulatory scheme for telecommunications and the prices it allows incumbents to charge competitors for access to the local network. Both impacts occur through indirect channels. As described previously, RORR and price cap regulation lead to differing incentives to deploy new products—in this case, DSL. While the cable companies’ decisions to offer broadband is not directly affected by public utility regulation in the U.S., any regulation affecting the deployment of DSL will indirectly affect the market for cable modem service, because they are substitutable to some degree. Prieger and Lee (2008) examine broadband deployment data for the entire U.S. and find that areas under RORR have a lower probability of broadband availability than areas under price caps or rate moratoria. The impact of the form of regulation is not large, however. After controlling for which firm is the local incumbent, the presence of competition, and a host of demographic and economic characteristics of the area, price caps and rate freezes are each associated with an increase in the probability of broadband deployment in the postal code area of about one percentage point. Compare the increase with an average deployment of broadband in the ZIP code of 75% in 2000, the vintage of the data used. Broadband services are often not subject to either price caps or rate freezes even when basic telecommunications services are. So, it is perhaps not surprising that the evidence is consistent with rate of return regulation (in which revenue from all sources is typically regulated) dampening the incentive to deploy new services compared to alternative regulation. The correlation found in Prieger and Lee (2008) may not be causal for a host of the usual reasons, as they discuss. Regulatory regimes are not randomly assigned, alternative regulation may be offered to companies in exchange for commitments to roll out advanced services, and companies favored with alternative regulation may wish to “demonstrate”

Is Regulation a Roadblock on the Information Highway?

its beneficial effect to the regulator by speeding broadband deployment. The other way states may indirectly affect broadband is through policy toward UNE rates for the parts of the local network. States do not set UNE rates unless negotiations between the private parties break down, but the threat of state rate setting affects the relative negotiating positions of the players. Pindyck (2007) notes that competitive local exchange carriers (CLECs) have a significant advantage in bargaining. If the parties are unable to agree on a rate, then the state regulator will typically impose a relatively low price to ensure CLECs can effectively compete in the market. The effect of UNE rates on broadband is indirect, because an ILEC’s DSL packet-switching facilities are not subject to unbundling. However, competitors wishing to offer DSL to subscribers without duplicating the local network could also purchase the “last mile” segment between the incumbent’s wire center and the subscriber’s premises as a UNE. Since DSL does not require the whole line, until 2003 competitors could “line share” with the incumbent by renting just the high-frequency part of the local loop as a UNE to offer DSL. These various forms of unbundling enable competition in DSL. Cable companies, in contrast, have never been required to open their networks to competitors. The empirical literature on the impact of unbundling on performance and competition is sizable, and here we cover only those empirical studies examining broadband innovation.14 The impact of unbundling policies directed toward a subset of the industry may not be as important in general as competition itself between cable and telephone companies. Howell (2002) and Maldoom, Marsden, Sidak, and Singer (2003) use sets of national case studies to find that unbundling is less successful than intermodal competition at speeding broadband deployment in developed nations.15 In another international comparison, Wallsten (2006) finds no relationship between full-loop unbundling requirements and broadband

penetration, but that sub-loop unbundling is correlated with lower penetration.16 García-Murillo and Gabel (2003) likewise find no impact of unbundling requirements on broadband availability within a country or on the percentage of population with broadband access. Relying solely on data from the U.S., Wallsten (2005) concludes that where more UNEs are rented, lower broadband penetration results. Curiously, he finds the opposite correlation for lines that are resold instead of purchased as unbundled elements, which casts doubt upon a purely causal explanation for either result.17 The sole study we found that associates unbundling with increased broadband access is García-Murillo (2005), which uses a small international cross-section of countries.18 Should we expect high or low UNE rates to stimulate broadband? Hausman (2002) argues forcefully that allowing competitors to rent facilities after they are deployed by the incumbents causes the incumbents to invest less in infrastructure. He attributes the early lead of cable modem service over DSL to the former’s closed networks. In Hausman’s (2002) view, low UNE rates retard the spread of broadband, at least among incumbent carriers. In accord with this notion, the rate of DSL subscription growth rose markedly after the FCC’s line-sharing rule was lifted in 2003 (Hazlett & Bazelon, 2005), although it is impossible to assess from a simple before-and-after comparison whether the change is entirely causal. Burnstein and Aron (2003) use state broadband subscription rates to indicate that lower UNE rates discourage broadband, although their estimate is not statistically significant. On the other hand, lower UNE rates encourage entry by competitors, thus spurring competition that may spill over to the broadband market as well (García-Murillo & Gabel, 2003; Ford & Spiwak, 2004). Partially supporting this conclusion, Distaso, Lupi, and Manenti (2006), using data from Europe, and Prieger and Lee (2008), using U.S. data, find that areas with lower UNE rates are correlated with more broadband availability,

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Is Regulation a Roadblock on the Information Highway?

but the sizes of the effects are small (although statistically significant). The latter study has the largest sample size and number of control variables of any, and furthermore controls for all state-level variables that do not vary over time in the econometric model. Further investigation reveals that the effects of UNE rates on broadband are greatest in states with alternative regulation. Thus, although the evidence in the literature is mixed, perhaps the tentative conclusion at this date is that UNE rates have little measurable impact on broadband deployment.

Conclusion and outlook For policymakers attempting to improve current regulatory schemes, the limited research available on innovation presents a problem. Each regulatory setting is unique, and thus presents unique incentives to participating firms. The external validity of the case studies is unknown, and not all instances of regulation have been thoroughly studied. What then can we conclude? Fortunately, a consensus exists in the economic literature and some general lessons are clear. In short, heavier regulation does place roadblocks on the information highway. Incentive regulation appears to spur process and product innovation. Whether examining total deregulation (Mueller, 1993), incentive regulation (Prieger, 2001), or regulatory delay (Hausman, 1997; Prieger 2001,2002,2007), studies typically find a negative relationship between the number of roadblocks created by government regulation and the amount of product innovation. While some studies may be picking up a demonstration effect in part, as long as the regulator periodically reviews the firms’ performance under the lighter regulatory regime and maintains the threat of re-instituting heavier-handed regulation (as was done in Indiana a few years past, for example), the improved innovation should continue. However, the regulator must avoid the temptation to

26

use periodic reviews to confiscate excess returns created by process innovation, for then dynamic efficiency is lost in the name of short-term, static welfare gains. Innovation and dynamic efficiency, however, are not the only goals of regulators. On the contrary, regulators are often instructed by legislation to strive toward competing goals, such as efficiency and universal service, and must find a balance. Rather than reading our review as necessarily calling for complete deregulation, policymakers should instead treat it as pointing out some of the dynamic costs of regulation of which they may not have been adequately aware. As regulators attempt to balance competing factors, however, they will find that the large potential costs from lost innovation often tip the scales in the direction of lighter regulation. These costs are higher in times of rapid technological change, such as the industry now finds itself in. The trend in telecommunications is toward convergence of voice, data, and video communication. Regulatory schemes that discriminate between the types of information communicated (e.g., FCC distinctions between information and telephone services) or the mode of carriage (e.g., cable systems vs. the telephone network vs. the Internet) based on the arbitrary historical accretion of rules are sure to fail to promote dynamic efficiency to its greatest extent. For example, when voice communication via VoIP (voice over Internet protocol) is carried over the cable system’s network on one end to the Internet and terminated on the telephone network on the other end, is it a telephone call? Or is it just transmission of data? A more appropriate question: why should it matter? Rules that force regulators to split increasingly fine hairs to categorize services and providers are bound to hamper investment in new technology and services and to favor less efficient technology or carriers over more efficient in some cases. Banerjee et al. (2007) discuss principles for future regulation to be guided toward the goal of dynamic efficiency. In the era of rapid techno-

Is Regulation a Roadblock on the Information Highway?

logical change and convergence, good regulation consists of reversing the regulator’s past emphasis on static efficiency to the detriment of dynamic efficiency. Instead of trying to force prices down to their long-run competitive levels immediately, or attempting to pick (and thus artificially creating) technological winners through asymmetric regulation, dynamically efficient regulation seeks to remove entry barriers wherever possible to allow unhindered intermodal competition. As technology such as the Internet erodes the monopoly bottlenecks remaining in the telecommunications network, intermodal competition becomes ever more feasible. However, removal of barriers need not be carried forward into creating “negative entry barriers” by providing artificial advantages to intramodal competitors (as some claim the unbundling rules have done for wireline telephony in the U.S. [Hausman, 2002]). Promoting inefficient entry at the expense of incumbents does not enhance dynamic efficiency and innovation. The challenge for regulators in the future will be to “do no harm” as they seek to level the playing field to let all participants compete, without imposing a priori notions of neutrality of outcomes that stifle innovation. Without entry barriers in the market, dynamic efficiency will help solve the problem of static efficiency as competition moves prices toward their efficient level.

References Ai, C., & Sappington, D. E. M. (2002). The impact of state incentive regulation on the U.S. telecommunications industry. Journal of Regulatory Economics, 22(2), 133-159. Arrow, K. (1962). Economic welfare and the allocation of resources for inventions. In R. Nelson (Ed.), The Rate and Direction of Inventive Activity (pp. 609-625). Princeton, NJ: Princeton University Press. Banerjee, A., Madden, G., & Tan, J. (2007, January) Regulatory trends: New enabling environ-

ment. Paper presented at the ITU New Initiatives Programme workshop on “The Future of Voice”, Geneva. Retrieved March 30, 2008, from http:// www.itu.int/osg/spu/ni/voice/papers/FoV-Madden-Banerjee-Tan-Draft.pdf Bourreau, M., & Doğan, P. (2001). Regulation and innovation in the telecommunications industry. Telecommunications Policy, 25(3), 167-184. Burnstein, D. E., & Aron, D. J. (2003). Broadband adoption in the United States: An empirical analysis. In A. L. Shampine (Ed.), Down to the wire: Studies in the diffusion and regulation of telecommunications technologies (pp. 119-128). New York: Nova Science Publishers. Cabral, L. M. B., & Riordan, M. H. (1989). Incentives for cost reduction under price cap regulation. Journal of Regulatory Economics, 1(2), 93-102. Crandall, R. W., & Jackson, C. L. (2003). The $500 billion opportunity: The potential economic benefit of widespread diffusion of broadband internet access. In A. L. Shampine (Ed.), Down to the wire: Studies in the diffusion and regulation of telecommunications technologies (pp. 155-193). New York: Nova Science Publishers. Distaso, W., Lupi, P., & Manenti, F. (2006). Platform competition and broadband uptake: Theory and empirical evidence from the European Union. Information Economics and Policy, 18(1), 87-106. Dixit, A.K., & Pindyck, R.S. (1994). Investment under uncertainty. Princeton, NJ: Princeton University Press. Faulhaber, G. R. (2002). Broadband deployment: Is policy in the way? In R. W. Crandall & J. H. Alleman (Eds.), Broadband: Should we regulate high-speed Internet access? (pp.223-244). Washington, DC: AEI-Brookings Joint Center for Regulatory Studies. Flamm, K. (2005, February). The role of economics, demographics, and state policy in broadband

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availability. Paper presented at the PURC/London Business School Conference on “The Future of Broadband: Wired and Wireless, 2005”, Gainesville, FL.

Hausman, J., & Sidak, G. (2005). Did mandatory unbundling achieve its purpose? Empirical evidence from five countries. Journal of Competition Law and Economics, 1(1), 173–245.

Ford, G. S., & Spiwak, L. J. (2004). The positive effects of unbundling on broadband deployment (Policy paper No. 19). Washington, DC: Phoenix Center for Advanced Legal & Economic Public Policy Studies. Retrieved March 30, 2008, from http://www.phoenix-center.org/pcpp/PCPP19Final.pdf

Hazlett, T., & Bazelon, C. (2005). Regulated unbun­dling of telecommunications networks: A stepping stone to facilities-based competition? Paper presented at the 33rd Telecommu­nications Policy Research Conference, Arlington, VA.

García-Murillo, M. (2005). Inter­national broadband deployment: The impact of unbundling. Communications & Strategies, 57, 83-105. García-Murillo, M., & Gabel, D. (2003, September). Inter­national broadband deployment: The impact of unbundling. Paper presented at the 31st Telecommu­nications Policy Research Conference, Washington, DC. Gayle, P., & Weisman, D. (2007). Efficiency tradeoffs in the design of competition policy for the telecommunications industry. Review of Network Economics, 6(3), 321–341. Greenstein, S., McMaster, S., & Spiller, P. (1995). The effect of incentive regulation of infrastructure modernization: Local exchange companies’ deployment of digital technology. Journal of Economics and Management Strategy, 4(2), 187–236.

Howell, B. (2002). Broadband uptake and infra­ structure regulation: Evidence from the OECD countries (Working Paper BH01/01). Wellington: New Zealand Institute for the Study of Competition and Regula­tion. Hu, W.-M., & Prieger, J. (2008). The timing of broadband provision: The role of competition and demographics. In Y.K. Dwivedi, et al. (Eds.), Handbook of Research on Global Diffusion of Broadband Data Transmission (pp. 241-259). Hershey, PA: IGI Global. Joskow, P., & Rose, N. (1989). The effects of economic regulation. In R. Schmalensee and R. Willig (Eds.), Handbook of Industrial Organization, 2, 1449-1506. Amsterdam: North-Holland. Kahn, A., Tardiff, T., & Weisman, D. L. (1999). The Telecommunications Act at three years: An economic evaluation of its implementation by the Federal Communications Commission. Information Economics and Policy, 11(4), 319-365.

Hausman, J. (1997). Valuing the effect of regulation on new services in telecommunications. Brookings Papers on Economic Activity, Microeconomics, 1-38.

Kolbe, A. L., & Tye, W. B. (1990). The Duquesne opinion: How much “Hope” is there for investors in regulated firms? Yale Journal on Regulation, 8(1), 113-157.

Hausman, J. (2002). Internet-related services: The results of asymmetric regulation. In R. W. Crandall & J. H. Alleman (Eds.), Broadband: Should we regulate high-speed Internet access? (pp.129-156). Washington, DC: AEI-Brookings Joint Center for Regulatory Studies.

Kridel, D., Sappington, D. E. M., & Weisman, D. L. (1996). The effects of incentive regulation in the telecommunications industry: A survey. Journal of Regulatory Economics, 9(3), 269-306.

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Lee, C. H. (2001). State regulatory commission treatment of advanced services: Results of a survey. Columbus, OH: National Regulatory Research Institute.

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Lyon, T. P., & Huang, H. (1995). Asymmetric regulation and incentives for innovation. Industrial and Corporate Change, 4(4), 769-776.

et al. (Eds.), Handbook of Research on Global Diffusion of Broadband Data Transmission (pp. 241-259). Hershey, PA: IGI Global.

Maldoom, D., Marsden, R., Sidak, J. G., & Singer, H. J. (2003). Competition in broadband provision and its implications for regulatory policy. Retrieved March 30, 2008, from http://ssrn. com/abstract=463041

Resende, M. (2000). Regulatory regimes and efficiency in US local telephony. Oxford Economic Papers, 52, 447-470.

Mueller, M. L. (1993). Telephone companies in paradise: A case study in telecommunications deregulation. New Brunswick, NJ: Transaction Publishers. Oppenheim, J. (1991). In B. G. Cole (Ed.), After the breakup: Assessing the new post-AT&T divestiture era, (pp. 310-315). New York: Columbia University Press. Pindyck, R. (2007). Mandatory unbundling and irreversible investment in telecom networks. Review of Network Economics, 6(3), 274-298. Prieger, J. E. (2001). Telecommunications regulation and new services: A case study at the state level. Journal of Regulatory Economics, 20(3), 285-305. Prieger, J. E. (2002). A model for regulated product innovation and introduction with application to telecommunications. Applied Economics Letters, 9(10), 625-629. Prieger, J. E. (2004). Regulation, innovation, and the introduction of new telecommunications services. Review of Economics and Statistics, 84(4), 704-715. Prieger, J. E. (2007). Regulatory delay and the timing of product innovation. The International Journal of Industrial Organization, 25(2), 219236. Prieger, J. E. (2008). Product innovation, signaling, and endogenous regulatory delay. Journal of Regulatory Economics, 34(2), 95-118.

Riordan, M. H. (1992). Regulation and preemptive technology adoption. RAND Journal of Economics, 23(3), 334-349. Sappington, D. E. M., & Weisman D. L. (1996). Potential pitfalls in empirical investigations of the effects of incentive regulation plans in the telecommunications industry. Information Economics and Policy, 8(2), 125-140. Tardiff, T., & Taylor, W. E. (1993). Telephone company performance under alternative forms of regulation in the U.S. National Economic Research Associates. Taylor, W. E., Zarkadas, C. J., & Zona J. D. (1992, June). Incentive regulation and the diffusion of new technology in telecommunications. Paper presented at Ninth Annual Conference, International Telecommunications Society, SophiaAntipolis, France. Wallsten, S. (2005). Broadband penetration: An empirical analysis of state and federal policies (Working Paper 05-12). Washington, DC: AEIBrookings Joint Center for Regulatory Studies. Wallsten, S. (2006). Broadband and unbundling regulations in OECD countries (Working Paper 06-16). Washington, DC: AEI-Brookings Joint Center for Regulatory Studies. WEFA Group (1995). Economic impact of deregulating U.S. communications industries. Bala Cynwyd, PA: The WEFA Group. Willig, R. (1976). Consumer’s surplus without apology. American Economic Review, 66(4), 589-597.

Prieger, J. E., & Lee, S. (2008). Regulation and the deployment of broadband. In Y.K. Dwivedi, 29

Is Regulation a Roadblock on the Information Highway?

Key Terms BOC: Bell Operating Company. The BOCs in the U.S. were the large ILECs created when AT&T was split up in 1984. CLEC: Competitive Local Exchange Carrier. A CLEC is a public telephone company that provides local telecommunications service in competition with the ILEC. Consumer Surplus: The benefits for buyers created by consumption of a good or service, net of the purchase price, denominated in currency units. Consumer surplus is created when a unit is consumed at a price less than the maximum willingness to pay for it. DSL: Digital Subscriber Line, a technology that provides a dedicated digital circuit between the local telephone company’s central office and an end-user’s premises, allowing broadband data transmission over existing telephone lines.

UNEs are purchased at wholesale rates from the incumbent telephone companies. UNEs include the local loop, switch port, switching, transport, signaling systems and databases (such as operations support systems and directory assistance). UNE-Platform (UNE-P, generally no longer available in the U.S.) combined all elements necessary to offer local service.

Endnotes 1



2



Deadweight Loss: potential economic surplus that is not realized by any participant in a market. ILEC: Incumbent Local Exchange Carrier. A public telephone company in the U.S. that provides local telecommunications service. Process Innovation: Innovation that lowers costs through the creation or adoption of new technology. Product Innovation: Innovation that makes new products or services available to consumers. RORR: Rate of Return Regulation. The most common historical form of telephone regulation in the U.S., in which the return on capital invested by the firm is limited to a “fair” rate. UNE: Unbundled Network Element. UNEs allow CLECs to offer competitively priced alternatives to the incumbent’s services rapidly.

30

3



4



5



6



Areas under the demand curve, such as the Harberger and Dupuit triangles, are only approximations of consumer welfare when there are income effects in demand. However, as long as the income effects are not too strong, they are good approximations in many cases (Willig, 1976). Given the paucity of formally peer-reviewed, published research, we cast a wider net than is often seen in such literature reviews. The reader is cautioned that some of the working papers and other unpublished studies we cite may not have undergone rigorous peer review. This is particularly true of the section on the broadband market below. We have undoubtedly missed some research, and welcome readers bringing omissions to the attention of the first author. For more sophisticated modeling of a regulated firm’s incentives to innovate, see Riordan (1992), Lyon and Huang (1995), and Prieger (2007,2008). The cases revolved around the FCC’s Computer III series of orders, stretching from the California I decision rendered in June 1990 until the California III decision of October 1994, when Computer III was remanded. The term “option” comes from the real options literature, in which the option value of delaying risky investment is priced into the firm decision problem (Dixit and Pindyck,

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7

8





9

10



11



12

13





1994). The adjective “free” does not mean that the competitors bear no costs of entry using UNEs, but instead that they are not required to pay for the risk reduction that UNEs offer them. See Hausman (2002) for the argument applied to DSL infrastructure. Kahn, Tardiff, and Weisman (1999) argue, to the contrary, that RORR encourages innovation by reducing the risks involved, since the firm is guaranteed a specified return on R&D. Incentive regulation may reduce costs by means other than process innovation, however. The famous Averch-Johnson effect, for example, maintains that a firm choosing its input mix under RORR will not minimize costs given the output produced and its current technology. See also work by Resende (2000), who estimates a yearly “efficiency score” (a measure of how productively a firm uses inputs) for U.S. ILECs. He then regresses the scores on regulatory variables to find that alternative regulation is robustly and significantly correlated with better efficiency. Endogeneity of an explanatory variable occurs when it is correlated with the econometric error term, which violates a fundamental assumption of ordinary least squares regression. For example, if incentive regulation is more likely to be adopted in poorer performing areas, then incentive regulation may be correlated with worse outcomes in a regression, even though the true causal impact is in the other direction. Ai and Sappington (2002) discuss the issue thoroughly and provide a solution. Nevertheless, see WEFA Group (1995) for a bold attempt. This section draws on Prieger and Lee (2008). Subscription rates reflect both innovation (in the sense of diffusion: where the service

14



15

16

17







18



19



20



is available) and other factors, such as the usual supply and demand considerations for existing markets. Much of the literature on UNEs looks at whether unbundling leads to investment in infrastructure by incumbents and facilities-based entry by competitors. See also Hausman and Sidak (2005), who discuss arguments for whether unbundling leads to more innovation. They conclude unbundling did not lead to innovation in the five cases they study. See also Distaso et al. (2006) for further evidence that intermodal competition is an important driver of broadband penetration. In full loop unbundling, the entire “last mile” of copper between the wire center and the subscriber is rented to the competitor. Sub-loop unbundling entails renting access to only the last part of the “last mile,” which in the case of DSL can allow superior transmission performance. Federal regulations require that any service that the incumbent local exchange company offers to retail customers has to be offered to CLECs at wholesale prices. These rules are distinct from the unbundling regime and UNE rates. In the estimation where García-Murillo (2005) finds a statistically significant positive effect of unbundling on broadband usage, there are 12 variables in the regression but only 18 observations, resulting in a nearperfect fit (R2 = 0.98). We treats costs and revenue as known quantities here. If they are uncertain, there is no change needed in our discussion if the firm is risk neutral. If the firm is risk averse, regulation has additional effects on the firm’s decision problem (see, e.g., Prieger, 2007). In mathematical terms, the effect on the amount of innovation of a(n infinitesimally) small increase in c is M′(c) = −m(c).

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Is Regulation a Roadblock on the Information Highway?

appendix Here we explicate the model, alluded to in the text, of how regulation indirectly affects innovation. Consider the panoply of new goods that a regulated firm could potentially offer. Potential goods differ in the amount of operating profit they will provide.19 Let the density m of operating profits R describe ∞ the distribution of potential outcomes, so that M ( x) = ∫ m( R)dR is the number of projects that earn x more than x. Assume in our simple model that the innovation cost c, which includes everything from basic research through development and product launch costs, is the same for all projects. Then the amount of innovation in which the firm chooses to engage is M(c), for only projects to the right of c are profitable (see Figure 2). The extra costs that regulation creates for innovators (examples of which are given in the chapter) increase c. The effect on the amount of the firm’s innovative activity is clear: as c shifts to the right in Figure 2, there are fewer worthwhile projects to pursue, M(c) decreases, and there is less product innovation. However, it is important to note that if regulation induces only a small change in c, then there will be only a small effect on innovation. Only those products that were barely profitable that are lost because of regulatory costs. How many such projects are not pursued depends on the density of projects near c.20 Regulation also can affect the benefit side of an innovator’s calculations. In this chapter we give many examples of how regulation reduces the revenues expected to follow from new products. In terms of the model, the density curve for operating profit shifts left (perhaps also changing shape) when this happens The net effect of regulation’s influence on the costs and benefits of introducing new products is shown in Figure 3. First, consider costs. As regulation increases costs from c0 to c1, the mass of innovation that becomes unprofitable is depicted by the horizontally striped area. Next, note that the vertically striped area is the mass of new products that become unprofitable due to the leftward shift of operating profit curve M. It can be seen that changes in the revenue of potential services may have a larger effect on the amount of innovative activity of the firm than changes in cost. Changes in cost affect only the marginally profitable services, whereas changes in revenue affect the mass of all formerly profitable services.

Figure 2. The determination of the amount of innovation m(R)

M(c)

c

32

R

Figure 3. Changes in the amount of innovation due to regulation

33

Chapter III

Reforms in Spectrum Management Policy Claudio Feijóo Universidad Politécnica de Madrid, Spain José Luis Gómez-Barroso Universidad Nacional de Educación a Distancia (UNED), Spain Asunción Mochón Universidad Nacional de Educación a Distancia (UNED), Spain

Abstract Wireless/mobile technologies are absolutely necessary for any agent who wants to participate in the new information and communication technologies market playfield. The means for the deployment of the wireless/mobile technologies is the radio spectrum. Thus, a rational assignment and an efficient use of radio spectrum become sine qua non condition for the sector development. The objective of this chapter is to present the reforms in the radioelectric spectrum management mechanisms that are currently being drafted (or that are even being applied) as well as to assess their advisability and timeliness. In particular, the chapter assesses the three deepest changes that are being considered: authorisation of the secondary market, usage of auctions for primary allocation and full liberalisation of spectrum usage.

INTRODUCTION As users’ demand for access to contents and applications moves towards a scenario characterised by mobility and ubiquity, the aim of integrating the provision of services and business models into a single structure becomes increasingly both necessary and attractive. This is the idea that lies behind the concept of Next Generation Networks

(NGN). Very simply speaking, a NGN is a single network that delivers multiple applications (voice, data, video) to multiple devices, whether fixed or mobile. Therefore, the deployment of the NGNs is the technical and business element around which the future evolution of the information and communication sector revolves. This upcoming scenario will be characterised by the fading of the boundar-

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Reforms in Spectrum Management Policy

ies between previously separate markets, because no access technology by itself (at least with the technical conditions expected as of today) could present the optimal characteristics for satisfying all the requirements involved in the NGN concept. In particular, wireless/mobile technologies are absolutely necessary for any agent who want to create (or to update) technological platforms capable of thriving in the new playfield. The means for the deployment of the wireless/mobile technologies is the radio spectrum. Thus, a rational assignment and an efficient use of radio spectrum become sine qua non condition for the sector development. The management of spectrum (the set of rules that govern the conditions to access it, the requisites for its usage and the rights it entitles) will define the characteristics and sustainability of future information and communications technologies (ICT) markets. Moreover, the consequences of the decisions about spectrum planning and management go beyond the sector. The innovation introduced in ICT markets regarding new services and applications hugely depends on the strategy followed by the operators which is reliant on market conditions. As just said, those strategies are conditioned by the spectrum regulatory framework. The knockon effects, undoubtedly, will affect general users and, particularly, business organisations for which communications services are becoming a key strategic asset, no matter the sector of economic activity. The objective of this chapter is to present the reforms in the radioelectric spectrum management mechanisms that are currently being drafted (or that are even being applied) as well as to assess their advisability and timeliness. The paper is structured into six sections. Section 2 details what could be considered as the “traditional spectrum management model”. Next, the reasons that make advisable a change of model are analysed and the most outstanding features of the transformation are summarised. Sections 4 and 6 describe and assess the three deepest

34

changes that are being considered: authorisation of the secondary market, usage of auctions for primary allocation and full liberalisation of spectrum usage. The paper ends with the conclusions that result from the previous analysis as well as with a few personal recommendations serving as a guide for change.

THE TRADITIONAL SPECTRUM MANAGEMENT MODEL The traditional regulation of the radioelectric spectrum is conditioned by two assumptions: the radioelectric spectrum is a scarce resource (or at least a limited one) and it is also a valued good which is used in services that are essential to society: applications connected to security, defence and response to emergencies, telecommunications and radio broadcast, transportation, scientific research, etc. With these assumptions, the radioelectric spectrum is considered as a public domain good by practically all administrations worldwide. As a consequence, the procedures for granting the right to using it are strictly regulated. Basically, after planning the usage given to each frequency band and specifying the service that can use it and the necessary technology, the right of usage is granted to certain agents through administrative decisions detailing the obligations of the licensee . This system resolves the problems that may rise due to interference. Additionally, since the first step of the process, planning, is coordinated in supranational organisations, an acceptable (not always complete) global compatibility is guaranteed of the communication systems which also generates important economies of scale in the electronic device market. As compensation for the rights of usage granted to the licensees, they are usually expected to pay an annual fee (fixed or subject to their results) and, frequently, to meet other commitments (usually regarding network deployment or level of coverage).

Reforms in Spectrum Management Policy

THE NEED FOR A CHANGE of MODEL •

Objectives for Spectrum Management The main objective of any spectrum management mechanism is (or should be) reaching the greatest usage efficiency to the extent possible. This general principle of efficiency can be broken down into three dimensions: technical efficiency, economic efficiency, and social efficiency. Note that these concepts are applied to the allocating and management mechanisms, and not to the usage made by the agents of the spectrum they have been granted. •

•

Technical efficiency requires that the greater amount of frequencies be available to be used effectively in the provision of services1. This implies that, should there exist several technologies with which to offer a specific service under the same conditions, the one that uses the less resources (frequencies) should be the preferred option. Additionally, the guard bands should be reduced as technically feasible: that is, without this restriction leading to the interference between the different radioelectric signals making it impossible to make good use of certain bands. An economically efficient spectrum allocation is one in which there is no way to reallocate spectrum such that everyone is better off, all else being equal (Morris, 2005). That is, the economic efficiency would be maximum when, from the combination of possible uses of the resource (the spectrum), the one valid for “producing” the services optimising the usefulness of the agents present in the market was chosen. Thus, allocating spectrum to services and/or technologies that are not the most demanded by the market should be avoided. Also, the

rights of usage should be removed for those that have become obsolete. Social efficiency implies that the radioelectric spectrum should be used in those services or applications maximising the wellbeing of society. In this sense, certain bands of the spectrum must be allocated to activities such as research or security, activities that would be discarded if only the maximisation of business benefits (or even the usefulness of the consumer) were to be considered in the short term.

In all cases, the analysis should be extended by introducing a prediction of future development or, in other words, optimising a dynamic definition and not a simply static one, of the efficiency. Also worth noting is the interrelation that exists between the three dimensions. For example, an increase in the technical efficiency releases frequencies, thus allowing the entry of new agents or the introduction of new services; the resulting increase in competition results in benefits for the users or the society as a whole.

Characteristics of the New Scenario The gradual introduction of improvements and innovations both in the technologies for handling the radioelectric spectrum and in those that use it have caused deep changes in the markets. In turn, the changes in the markets have promoted research which, in a sort of virtuous circle, has boosted new technological changes. Although no causality can be established between the latter and former advances, what can indeed be considered is which of these transformations affect each of the three dimensions of efficiency in the usage of the spectrum: •

As regards the technical efficiency: Development of technologies that reduce the amount of spectrum required for sending the same amount

ο

35

Reforms in Spectrum Management Policy

•

36

of information. A paradigmatic and contemporary case is the transition from analog to digital format in terrestrial television broadcast. ο Introduction of dynamic spectrum access techniques (such as software defined radio or cognitive radio) allowing highly flexible management and (re)use2 of spectrum across all its dimensions (frequency, time, location and code) (refer to Nekovee, 2006). ο Appearance of technologies that use a very broad range of spectrum with, simultaneously, a very low emission of power (ultrawideband technologies), which causes a very small level of interference and its possible “coexistence” with other services operating on the same band. ο Innovations with repercussion in the access part of the networks (mesh networks, femtocells) allowing the reuse of frequencies and an increase of the efficiency in their usage. As regards the economic efficiency: ο Proliferation of services that require radioelectric spectrum for operating. ο Existence of services that have become obsolete and that use much more spectrum than would be necessary with other technological alternatives or, in the most extreme case, that do not use at all the frequency bands allocated (and that, as a consequence, should be reallocated). ο Growing usage of bands that do not require usage license, thus playing down the need for such a detailed planning. Not only growing, but successful as well: two examples are WiFi and Bluetooth. ο Fast evolution of the technology (not always predictable), thus hindering the a priori allocation of spectrum bands to

•

specific technologies which can become rapidly obsolete. As regards the social efficiency: ο Strategic importance of many services that require spectrum and that are considered to be tools that promote the development of the information society.

Keys for a New Model As opposed to these new circumstances, the traditional model appears as excessively complex and lacking flexibility. This fact has led to the appearance of a current of opinion favourable to the introduction of market economy criteria in radioelectric spectrum management3. In fact, many national authorities in charge of spectrum management4, the European commission5 or the ITU6, have released documents supporting the modification of the current spectrum management models and defending the inclusion of market mechanisms. Moreover, the reform of the regulating framework is already effective in several countries. The new ways of managing the spectrum intend to increase flexibility and transparency, as well as the speed of the response to technological innovations. The actual demand and the value given by the market to each band of frequencies are new governing criteria. Obviously, any change should improve global resource usage efficiency, while maintaining certain inalienable technical requirements. There are three possible paths leading to change. These are listed in ascending order in the process of allocating the spectrum usage rights: •

•

Modifications in the conditions of the allocated license: relaxation of some clauses but, especially, authorisation of the transmission of rights (secondary spectrum trade). Modifications in the license-allocation mechanisms: usage of auctions.

Reforms in Spectrum Management Policy

•

Modifications in the definition of the licenses: avoiding to bind the license to specific technologies (technological neutrality) or even to specific services (service neutrality).

These three paths do not represent different alternatives. Several of these tools can be chosen, and this could be done simultaneously as well as in succession. However, they are not completely independent, and as we will see below, the introduction of certain changes is almost unavoidably connected with other modifications of the model. Below we will analyse the characteristics of these eventual reforms.

SECONDARY SPECTRUM MARKET Concept “Trading the spectrum” represents the total or partial subrogation of the rights that have been awarded to an agent to make use of a segment of the public radioelectric domain. Trading creates a new way of accessing the spectrum. Interested companies can obtain the

rights of usage through the primary allocation, if they are chosen by the appropriate authority responsible for spectrum allocation, or through the secondary market, purchasing the rights of usage from another agent. The reasons that would lead an operator holding a usage license over the public radioelectric domain to subrogate it would be of an economic nature: said operator receives a remuneration from the agent acquiring the right (directly or indirectly, if the substitution is connected to other agreements between the two parties) or the transmission represents a cost reduction (for example, avoiding to have to pay the annual radioelectric fee or tax). On the other hand, the interest of the operator receiving the rights of usage for the spectrum can be quite varied: accessing a new market, acquiring additional spectrum in order to improve the provision of their services, avoiding the entry of new competitors, etc.

Modes of Transferring the Usage Rights Table 1 establishes a classification of the different criteria with which a right transfer could be carried out:

Figure 1. Spectrum management evolution (Source: Prepared by the author)

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Reforms in Spectrum Management Policy

Table 1. Modalities of usage rights transfer (Source: Prepared by the author) Criterion

Modalities

Peculiarities

Permanent

The subrogation is established for an unlimited time, with the granting agent permanently relinquishing the right of usage (irrevocable transfer)

Temporary Provisional

The subrogation is established for a period of time defined in the agreement

Total

The granting agent relinquishes the right of usage of the spectrum in the whole geographical scope of the license

Regional

The granting agent and the grantee share a part or all the frequency bands in different geographical areas

Complete

The grantee of the rights of usage has to subrogate in the rights and obligations of the granting agent

Partial

The granting agent maintains the obligations taken on before the Administration. It is essential to define the obligations acquired by the grantee, if any

Revocable

According to the conditions stipulated, the granting agent can revoke the right transfer

Irrevocable

The granting agent permanently relinquishes the right of usage of the spectrum

Geographical

Frequency bands

Revocability

All the categories in Table 1 imply the relinquishment of the granting operator of all or part of their rights. In the so-called right “sharing”, the spectrum is used by two operators without this representing a substantial reduction of the conditions of usage of the first holder. The conditions for a shared usage of the spectrum have their limit in the “supportable interference” or maximum level of noise generated by the new user that does not disturb the service of the original band holder. This modality is tightly related to the new possibilities offered by the technological progress mentioned previously, such as the ultrawideband or intelligent radio techniques.

•

•

Advantages and Disadvantages Resulting from Trading the Spectrum Opening the radioelectric spectrum to the market can provide a series of advantages: •

38

Increase of the technical efficiency in the usage of the spectrum: the agents will have incentives to make a more efficient usage of the spectrum they have been granted, minimizing the amount of spectrum they

require for providing their services and putting the rest on the market. Increase in competition: the increase of the technical efficiency represents indirectly the increase of the available spectrum and, as a consequence, of the amount of service offering agents. Promotion of innovation: the establishment of a free exchange system allows for technological innovations to reach the end user earlier, since on the one hand the companies with rights of usage of the spectrum have incentives to introduce said innovations and, on the other hand, the new operators have a mechanism to enter the markets which is much faster and flexible than the primary frequency allocation.

As opposed to the potential advantages sketched out previously, the secondary spectrum market poses some problems which should be considered before determining the spectrum granting procedure: •

Generation of uncertainties: the grant of the spectrum modifies the competition condi-

Reforms in Spectrum Management Policy

•

•

•

tions established implicitly in the primary spectrum allocations, where the total number of licenses were specified, providing the market with a certain degree of stability which favoured the commitment of investments. Distortion of the competition: certain agents can make the most of the frequency granting to accumulate spectrum and thus achieve positions of market domination. Additionally, agents could appear that operate with merely speculative intentions, rising the price of the spectrum without providing any value neither to its management nor to its efficient usage. Appearance of other market failures: failures regarding the concepts of social and technical efficiency (conflicts due to interference, difficulties for the development of standards), and also due to the costs of transaction. For Valletti (2001), “one should not only question how serious these failures are, but also if the regulator would be able to find better solutions than the market”. Inefficiency in the usage of the resource: an excessive fragmentation of the spectrum could originate a significant increase of the unavailable frequencies as they would be used as guard bands. Additionally, international coordination problems could appear, or merely regional ones, should the frequency grant be geographically limited.

MODIFICATION OF THE PRIMARY ALLOCATION METHOD: THE AUCTION Characteristics of the Spectrum Auctions Tenders have been the predominant mechanism (although not the only one7) for primary spectrum allocation. The tender allows the regulator to de-

termine through economic criteria, among others (also social, even technical), which applicant is better qualified to use the spectrum. Despite the aforementioned, the usage of auctions is not unknown in the sector. Licenses have been auctioned for years and in a great deal of countries. However, there was a point of inflection in the consideration of auctions as a spectrum allocation mechanism. During 2000 and 2001, several European countries auctioned third generation (3G or UMTS) mobile-communications licenses. The amount reached by the bids8 even led the spectrum auctions to make the headlines in the media. Since then, research on auctions started proliferating, attempting to reach the optimum allocation mechanisms for the spectrum in terms of efficiency as well as of revenue maximization because of the fact that the design of the auction model fully conditions the results obtained from the award process (Banks et al., 2003; Milgrom, 2004; Plot and Salmon 2004). When there are multiple objects to be sold, like spectrum licenses, the seller has many options to consider. The first decision the agency in charge of managing the spectrum must take is whether to sell the objects separately in multiple auctions or jointly in a single auction. •

The main formats if licenses are sold in different auctions are9: ο Sequential auctions: Licenses are sold one at a time in separate auctions. ο Simultaneous auctions: Groups of related licenses are sold at the same time in different auctions and bidders can bid on any of the items. All auctions would close at the same time when no new bids are received in any license for a period of time. The Simultaneous Multiple-Round (SMR) Auctions (also called the Simultaneous Ascending Auction) have discrete, successive rounds and participants submit a se-

39

Reforms in Spectrum Management Policy

•

40

ries of single-item bids for the desired licenses. Then, the high bids for each license become the standing prices for the next round of bidding. The auction ends when no new bids are posted in a round in any license. If the seller chooses to sell all the licenses at a time in a single auction (especially when the items are not completely homogeneous), they must face the question about how to package the goods offered for sale. The usual standard consists in allowing the bidders to choose the packages for themselves. This type of auctions are known as combinatorial or package auctions, and among them, the following stand out (Cramton et al., 2006): ο Iterative combinatorial auctions: At the beginning of each round, bidders submit prices for one or more packages. Then the auctioneer solves the winner determination problem, announces provisional allocation and asks prices for the next round. The auction ends at a fixed deadline or when no new bids are submitted. ο Ascending proxy auctions: Bidders report their valuation about packages to a proxy agent. The proxy agent bids on the bidder’s behalf in each round. The auctioneer considers all bids (from present and past rounds) and chooses his best feasible collection of bids (at the most, one bid from each bidder). The auctioneer announces provisional allocation and the process continues until no new bids are submitted. ο Clock-proxy auction: Hybrid auction format that begins with a clock phase and ends with a final proxy round. In the clock phase, the auctioneer announces prices for each item being sold and bidders indicate the demanded quantities. Prices will continue going up until there are no items with excess demand. Then,

the auction finishes with a proxy round in which bidders submit their preferences to a proxy agent. This auction format combines the advantages of the clock phase (simple and transparent price discovery) and the proxy phase (efficiency and revenue maximization), mitigating the exposure problem10. Of these possible auction formats, the combinatorial ones are particularly appropriate if there are strong complementarities between licenses (synergies11) as well as substitution possibilities. These auctions allow the participants to bid both for complete packages (all-or-nothing bids) as well as for individual licenses. However, and despite these advantages, their usage is not yet generalised due to their complexity both for the auctioneer (in the solution of the winner determination problem) and for the bidders when placing their bids. In fact, the Federal Communications Commission (FCC), which has been conducting auctions of licenses for electromagnetic spectrum since 1994, uses SMR auctions12. As explained by Cramton et al. (2006), despite the SMR auction cannot be considered a combinatorial auction, most SMR auctions allow bidders to withdraw bids, mitigating the exposure problem and providing the bidders with the option of bidding for the licenses they are most interested in. Nevertheless, recently the FCC has also included the possibility of modifying the SMR auction allowing combinatorial or package bidding in some auctions.

Comparison Between Tender and Auction Below are analysed a series of items that appear in any debate between supporters of one or another method of allocation. However, it should be stated that the characteristics of the market in question and, especially, the design of the process (be it auction or tender) are basic parameters that could alter the general conclusions. A well planned ten-

Reforms in Spectrum Management Policy

der is always preferable to a deficient auctionm, and vice-versa. The objective would be thus to analyse which is the preferable method, assuming a correct design in both options. •



•





Tenders are accused of lacking transparency and credibility. Indeed, regardless of the rigour of the assessment criteria, the selection procedures include a subjective element, which is why they are sometimes known as beauty contests. This subjectivity usually rises the suspicion that the organisations in charge of making the decisions could carry out their obligations in a biased manner. Occasionally, the decisions are criticised, and even contested, thus affecting the credibility of the license awarding process and, generally, that of the responsible administration. Auctions, on the other hand, represent a transparent and objective way of awarding the licenses. As an argument against the auction, some adduce that the tender allows to allocate the spectrum to those operators with greater investment commitments, thus affecting the extension and quality of service or the creation of jobs. However, an appropriate prequalification procedure (including coverage and quality criteria) guarantees that the awardees of the auction will have the technical and financial capabilities required to quickly initiate service provision. Tenders lower the barriers of entry to the market for operators, since they do not request any prior payment in order to start operating (or, if they do so, the amount is much smaller). As a consequence, operators can carry out a rational distribution of the investment and have initially more economic resources to deploy infrastructures and develop services.



•

•



•



The same thesis can be turned around in the case of the auction: the expenditure required to win an auction can also be considered as an incentive for the fast expansion of the networks. In fact, this is the only way in which the winner of an auction can recover the investment (sunken cost) that represents the price paid for the license. Related to the prior argument, some object that winning operators in an auction will assign the cost of the license directly to the end services they offer. Or, in other words, that consumers will pay higher prices. It has not been proven whether this behaviour is possible with operators. In his study, Bauer (2003) concludes that “despite weak hints that license fees influence prices, no statistically significant evidence for lasting effects could be detected”. The tender creates economic income associated to the power of market created by limiting ex ante the number of agents present in the market (Hazlett, 2003). Nothing changes in the case of the auction, unless the license obtained is allowed to be transferred. A frequently used argument in favour of the spectrum auctions is that they provide the greatest income possible for the use of a public resource. This income could go to social plans in the industry itself (for example, financing the universal service). However, this is not an argument with absolute validity. Apart from the fact, of course, that collusive behaviours (where the bidders agree the price beforehand) must be avoided in the auction, the truth is that the income depends on the auction model and of the valuations and strategies of the bidders. Additionally, the result of the auction is always a mystery which would lead an administration with “aversion to risks” to prefer knowing beforehand what they would take and would chose the tender. In these

41

Reforms in Spectrum Management Policy

•



cases, the type of service is also a parameter for decision: in services with low demand, there could be less bidders than auctioned rights. Exogenous factors may appear (an economic depression, a new technology) that make difficult honouring the commitments taken on at the time of awarding a tender. It is not infrequent for deployment or service requirements to be included in auctions. In that case, nothing would be different from a tender. It is true that the relaxation or suppression of the obligations connected to the awarding of a license is linked to the use of the auction since it leaves the tender without parameters of decision.

basically three models for achieving this “full” liberalisation of the spectrum: •

•

In the “private property” model, the contents and duration13 of the usage rights are defined and a primary allocation of the latter is carried out. Once the licenses have been awarded, the agent holding the right has complete freedom of action14, with the only restrictions of higher-level regulations (commercial legislation or competition defence legislation). In the commons model, it is considered as a community resource and, thus, there are no particular usage rights defined15. Not even a formal license is required to operate. This is a modality which has already been applied to certain “free usage” bands, such as those used by WiFi. As an alternative between the two previous models, Faulhaber and Farber (2003) propose a private property model avoidable under conditions of non-interference. In this regime, the spectrum could be shared and sold without any more restrictions in the usage than those referred to the power of the emission. However, this right of usage would be preferential and non-absolute since any other agent would be entitled to emit on that band provided they met the condition of non-interference. It would be a mechanism similar to the commons one described in section 4.2 but without the need for a prior agreement. Thus, a usage regime would be established de facto which could known as a “conditioned commons”.

LIBERALISATION OF THE SPECTRUM USAGE

•

As stated in section 2, the allocation of a specific spectrum usage license involves obligations that are traditionally very strict: service to be provided, specific technology that must be used, limitations on the power of emission, geographic scope where broadcasts are allowed and bandwidth of each channel. Spectrum usage liberalisation allows for some or even all the aforementioned conditions to be relaxed or omitted, in a way that the agents that enjoy the rights over the public radioelectric domain are given the capability of deciding the usage and technology that they will implement. Technological neutrality (free choice of the technology with which to provide the service) does not present too many problems, both from the conceptual point of view and in practice, particularly if the technological alternatives, as is usually the case, do not present radically different emission characteristics. More complex (understood as more “revolutionary”) is the configuration of a spectrum regulating model also allowing service neutrality (free choice of usage given to the band). There are

The liberalisation of the spectrum usage faces, in any of its modalities, the problems that the traditional method of thorough allocation of services had resolved: global compatibility of communication systems, creation of standards (with the subsequent scale economies in the electronic device market) and prevention of interference.

42

Reforms in Spectrum Management Policy

The problem of interference is particularly acute in the case of the commons, and quite particularly if the usage is intensive and the resource becomes scarce (“tragedy of the commons”). The other two models resolve (at least partially) the problem but at the expense of increasing (maybe even extraordinarily) the transaction costs. Although the private actors become the stars in these models, there remains a role for the spectrum management organisations: monitoring that the users meet the public radioelectric domain protection conditions, controlling the exposure limitations for health protection, risk assessment for radioelectric emissions, controlling that negotiations between agents are led under a competition framework. As a rule of thumb, public ex ante intervention is minimised and ex post control increases.

•

•

•

Conclusion That the radioelectric spectrum needs a new management model (or at least a renewed one) is a consensus among public actors with interest in the market and researchers. Considering the analysis carried out in this chapter (and particularly the advantages and disadvantages presented in each case), a series of guidelines are proposed for the introduction of reforms in the spectrum management mechanisms: •



The reform must necessarily be progressive in depth (what measures), scope (what frequency band) and timetable. Regardless of its appropriateness, a full and immediate liberalisation of all the commercially useful spectrum is not feasible. This implies a progressive replacement of the ex ante regulation of the traditional scheme by a relaxed regulation (or a completely ex post one). The period of cohabitation between different models shall be long or even indefinite, since full liberalisation should not necessarily be the end objective.

•



The modifications in the spectrum management policy shall have significant effects on the market only in the medium-term. It is critical to design a scenario which, starting from the current situation, identifies the objectives (basically in terms of efficiency). It shall be necessary to periodically monitor the degree of achievement of the objectives, underlining the best practices and introducing the necessary corrective measures. The assessment should precede any reform, assuming the enormous complexity of the current occupation in each band. The analysis shall condition to a great extent the specific measures that may be applied. Particularly, it will be useful to select a series of pilot bands on which to test alternative models. Given the different characteristics presented by the different bands it may not be feasible to apply a single spectrum management model. As a consequence, it would be necessary to carry out an analysis on a band-by-band basis determining the basic management model that is more adequate for each one (of among the possible options of “traditional regulation”, “progressive introduction of market mechanisms” and “liberalised model”), and identifying the different services their usage can be dedicated to. The introduction of market mechanisms is compatible with fixing a series of technical and/or economic efficiency criteria useful for the control that the governmental and spectrum management organisations must exert. Thus, resource usage thresholds could be established in order to penalise those agents operating below the minimum level of efficiency, or, as a last resort and in cases of continuous inefficient usage, to revoke their rights of usage. This type of tool would also be useful in fighting against anticompetition practices such as the accumulation of

43

Reforms in Spectrum Management Policy

•

•

44

spectrum in order to establish entry barriers to the market. All the processes regarding spectrum management must be public. This implies the publication of the global strategy of the organisation in charge of the spectrum, the updated maintenance of the frequency record (including relevant information on the allocations: frequency, bandwidth, duration, date on which the allocation was granted and expiry date, service, possibility of secondary business, price) and information on the degree of usage of each band, on the efficiency criteria and on the conflict resolution procedures. Specifically, the frequency record is important for an effective introduction of the spectrum trade (refer to Bykowsky, 2003). In less general terms, and considering the specific situation of certain services or bands, the following corrective measures could be considered: ο The introduction of trading mechanisms should start from some “simple” bands, such as those dedicated to radiolinks. The experience gained here would later be applied to more complex bands for their offer–demand dynamics. ο Given the rise of some technologies that operate in common usage/licenseless bands (such as WiFi or Bluetooth), it would be necessary to investigate whether increasing the range of the spectrum dedicated to this type of usage would encourage the development of innovative applications. ο The “digital dividend” resulting from the television “analog blackout” represents a great opportunity for introducing some criteria attempting to increase the efficiency in the usage of the spectrum. ο The third generation (and similar or succesive) mobile communications

present an opportunity to provide the broadband access to to those regions or zones that are still devoid of this type of connections. The spectrum currently allocated to this service seems to be insufficient and operators should be given the opportunity to access new bands (be it “traditionally”, be it via the secondary trade).

References Ausubel, L. M., Cramton, P., McAfee, P., & McMillan, J. (1997). Synergies in wireless telephony: Evidence from the broadband PCS auctions. Journal of Economics and Management Strategy, 6(3), 497-527. Banks, J., Olson, M., Porter, D., Rassenti, S., & Smith, V. (2003). Theory, experimental and the Federal Communications Commission spectrum auctions. Journal of Economic Behaviour and Organization., 51(3), 303-350. Bauer, J. M. (2003). Impact of license fees on the prices of mobile voice services. Telecommunications Policy, 27(5-6), 417-434. Bykowsky, M. (2003). A secondary market for the trading of spectrum: promoting market liquidity. Telecommunications Policy, 27(7), 533-541. Coase, R. (1959). The Federal Communication Commission. The Journal of Law & Economics, 2, 1-40. Cramton, P. (2002). Spectrum auctions. In Cave, M., Majumdar, S. & Vogelsang, I. (Eds.), Handbook of Telecommunications Economics (pp. 605-639). Amsterdam: Elsevier Science. Cramton, P., Shoham, Y., & Steinberg, R. (2006). Combinatorial auctions. Cambridge: The MIT Press.

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Falch, M., & Tadayoni, R. (2004). Economic versus technical approaches to frequency management. Telecommunications Policy, 28(2), 197-211. Faulhaber, G. R., & Farber, D. J. (2003). Spectrum management: property rights, markets, and the Commons. In Cranor, L. F. & Wildman, S. S. (Eds.), Rethinking rights and regulations: Institutional responses to new communication technologies (pp. 193-226). Cambridge: The MIT Press. Hazlett, T. W. (2003). Liberalizing US spectrum allocation, Telecommunications Policy, 27(7), 485-499. Klemperer, P. (2002). How (not) to run auctions: The European 3G telecom auctions, European Economic Review, 46(4-5), 829-845. Marx, L. M. (2006). Economics at the Federal Communications Commission, Review of Industrial Organization, 29(4), 349-368. Milgrom, P. (2004). Putting auction theory to work. Cambridge: Cambridge University Press. Morris, A. C. (2005). Spectrum auctions: Distortionary input tax or efficient revenue instrument? Telecommunications Policy, 29(9-10), 687-709. Nekovee, M. (2006). Dynamic spectrum access – Concepts and future architectures. BT Technology Journal, 24(2), 111-116. Plot, C. R., & Salmon, T. C. (2004). The simultaneous ascending auction: Dynamics of price adjustment in experiments and in the UK 3G spectrum auction. Journal of Economic Behaviour and Organization, 53(3), 353-383. Spiller, P. T. & Cardilli, C. (1999). Towards a property rights approach to communication spectrum. Yale Journal on Regulation, 16(1), 53-84. Valetti, T. M. (2001). Spectrum trading. Telecommunications Policy, 25(10/11), 655-670.

Weiss, T. A. & Jondral, F. K. (2004). Spectrum pooling: An innovative strategy for the enhancement of spectrum efficiency. IEEE. Communications Magazine, 42(3), S8-S14. Werbach, K. (2004). Supercommons: Toward a unified theory of wireless communication. Texas Law Review, 82(4), 863-973. White, L. J. (2000). ‘Propertyzing’ the electromagnetic spectrum: why it’s important, and how to begin. Media Law & Policy, 9(1), 29-30.

Key terms Allocation: Allocation of a specific band of frequencies for their use by one or more services (terrestrial or spatial radiocommunication, or by the radio astronomy service) under specified conditions. Primary Spectrum Allocation: Allocation of rights of usage of the spectrum by the appropriate spectrum management authority. Frequency Band: Fraction of frequencies of the radioelectric spectrum that present similar characteristics as regards the propagation of the electromagnetic waves. Free Usage Band: Frequency band, the use of which is not subject to the possession of a license awarding usage rights. Secondary Spectrum Market: Market where the holders of spectrum usage rights transfer said rights to other agents. Technological Neutrality: Characteristic of frequency allocation processes specifying the service for which a specific band is to be used, but not the specific technology to be used for providing it. Service Neutrality: Characteristic of frequency allocation processes where the service

45

Reforms in Spectrum Management Policy

(and thus, the technology) to which a specific band is to be allocated is not specified. Radioelectric Spectrum: Limited natural resource made up by all the radioelectric waves (in the frequencies between 9 KHz and 3000 GHz) that propagates through space without the need for an artificial guide.

6



Endnotes 1



2



3



4





5



46

Which, in economic terminology, would represent being at the limits of the production possibilities (of resource usage). Consider that extensive spectrum usage measurements show that considerable parts of the spectrum, although dedicated to specific services, are actually not used for significant periods of time, ranging from seconds to minutes (Weiss and Jondral, 2004). Actually, it is a “reinforcement” and not an “appearance” of this current of opinion. As far as 1959, Coase already argued that the spectrum should be seen just as another production factor for which the value must be determined on the free market, while the interference problem should be solved by the regular private property right legislation (Coase, 1959). As an example in Europe, that of the British regulator OFCOM. Refer to the document “Spectrum framework review: Implementation plan” released in 2005 (available at http://www.ofcom.org.uk/consult/condocs/ sfrip/). On the other hand, the FCC quotes as their first objective in their Web site: “advance spectrum reform by developing and implementing market-oriented allocation and assignment reform policies”. Refer to http://www.fcc.gov/spectrum/ “Policy aims to facilitate spectrum access across the EU through market mechanisms”.

7



8



9



10





11

Communication of the Commission “i2010 – A European Information Society for growth and employment” COM (2005) 229 final. Brussels, 1.6.2005. Refer to, as an example, the ITU document “Market mechanisms for spectrum management”. A document that summarizes the results of a workshop with the same title held in Geneva, Switzerland, from 22 to 23 January 2007 (available at http://www.itu. int/osg/spu/stn/spectrum/workshop_proceedings/STN.MMSM-2007-PDF-E.pdf). Drawing of lots represents a fast, economic and transparent method for choosing from several prequalified applicants. Despite draws were used by the FCC until the nineties, they do not represent an efficient solution, since the winner of the licenses may not be the one who values them the most or who offers the most socially beneficial service and deployment plan. Measured by the income obtained by the Government, not all auctions had similar success. Actually, the results were extremely different from some countries to others, oscillating between the 20 euros per capita of Switzerland and the 650 euros per capita obtained in the UK auctions. This major dispersion was basically due to the poor auction design in some countries and to the time sequence in which the auctions were carried out (Klemperer, 2002). Cramton (2002) states the advantages and disadvantages of these auction models with open and sealed bids, in spectrum allocation. In the presence of synergies, bidders are affected by the exposure problem, as they can earn negative profits if they fail to win complementary objects. Synergies among licenses are classified according to Ausubel et al. (1997) as local and global synergies. Local synergies are those gains in value that specifically arise

Reforms in Spectrum Management Policy

12

13





from obtaining two or more geographically neighbouring licenses. Global synergies are those gains in value which accrue from obtaining increased numbers of licenses or markets: economies of scale or scope among multiple licenses which arise irrespective of their geographic locations. The Simultaneous Multiple-Round auctions fit in environments where bidders need to be able to shift their bidding among substitutes and to bid simultaneously on licenses that they would like to acquire together (Marx, 2006). Although it would be possible for the Government to effectively transmit the property of the right over the spectrum, this does not seem to be the most probable option (refer to the defence of this option in Spiller and

14



15



Cardilli, 1999, or in White, 2000). It would be expected that it was done for a specific number of years (even with the possibility of renewal) which, legally, would take the figure closer to a possession or to a right of usage and enjoyment. This would include the right to do business with the license. As stated in section 3, the reforms in the management of the spectrum are not completely independent and it does not seem conceivable in a framework where the usage liberalisation is introduced without the secondary market. “A universal communication privilege, allowing anyone to transmit anywhere, at any time, and in any way, should be the baseline rule for wireless communication” (Werbach, 2004).

47

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Chapter IV

Next Generation Access Networks and their Regulatory Implications Ricardo Gonçalves Universidade Católica Portuguesa (Porto), Portugal Álvaro Nascimento Universidade Católica Portuguesa (Porto), Portugal

Abstract The deployment of Next Generation Access networks (NGAs) is likely to have a significant impact on the telecommunications’ value chain and, consequently, on the necessary regulatory remedies. In particular, unlike existing telephone networks, NGAs present regulators with a dilemma, in so far as the possibility of regulatory intervention after network deployment (negatively) affects investment incentives for such a deployment. We review the current discussion surrounding NGAs and discuss some of the main regulatory challenges it presents.

INTRODUCTION Next Generation Networks are slowly but increasingly being used at the core of the public switched telephone network (PSTN). A Next Generation Network (NGN) is, according to the ITU, “a packet-based network able to provide services including Telecommunication Services”, i.e. a multi-service (voice, data, video or other media)

network based on packet-switching (as opposed to the traditional circuit-switching of the PSTN networks). But whilst the core network has been (or will be) replaced by a Next Generation Network, able to carry all those services, the access network has lagged slightly behind. As network operators deploy (or consider deploying) such Next Generation Access networks (NGAs), several interesting questions have to

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Next Generation Access Networks and their Regulatory Implications

be raised. From an operator’s perspective, it is important to understand how NGAs affect the value chain, for instance, by uncoupling service provision from specific network infrastructure requirements. In particular, vertical integration in the presence of NGAs appears to be a less sensible strategy than it is under existing telephone networks. From a regulatory perspective, NGAs are likely to be an economic bottleneck and, as such, regulatory intervention may be warranted. However, a dilemma presents itself: unlike current telephone networks, NGAs do not exist yet. It is natural to expect that the possibility of regulatory intervention after network deployment (negatively) affects operators’ incentives to deploy them in the first place. This paper is a survey of NGAs and their main regulatory implications. OFCOM, the UK telecommunications regulator, is (arguably) the institution which has given this topic more thought. Hence, it should not be surprising that we refer to its documents extensively. Additionally, the paper was written with a view to increasing awareness of the importance of NGAs in the telecommunications sector and, inevitably, to the regulatory challenges it presents. As such, we deliberately refrain from advocating a specific course of action, as we believe the discussion is still at the beginning.

WHAT IS A NEXT GENERATION ACCESS NETWORK? An access network, commonly referred to as the local loop, is the part of the telecommunications network which connects the subscriber to the local exchange, where switching equipment is installed. Traditionally, access networks consisted of copper wire connections used solely for telephone services. Recently, these copper wire connections have proved to be good carriers for additional services such as broadband connections.

Most broadband connections provided by telephone operators are xDSL connections. xDSL is a broadband technology which uses existing copper wired telephone networks to carry data traffic. The provision of xDSL services requires the network operator to install additional equipment in an exchange, so that voice traffic is separated from data traffic (they travel together along the copper-based access network). Data traffic is sent to the DSLAM (Digital Subscriber Line Access Multiplexer), the entry point in the IP network, which concentrates subscriber lines and their respective traffic. By far the most popular type of xDSL is ADSL, which provides more capacity downstream (from the network to the subscriber) than it does upstream (from the subscriber to the network). The problem with xDSL is that not all existing copper wired subscribers can benefit from it in the same way. The analysis of several xDSL products, such as ADSL2, ADSL2+, VDSL, HDSL1 or SDSL2, highlights a trade-off between maximum download speed and local loop length. For some types of xDSL (e.g. VDSL), that length is very small (up to 1.5Km), but can deliver maximum download (52Mbps) and upload (16Mbps) speeds which are much faster than ADSL. These speeds make the provision of triple play services – three communications services (voice, data and television) over a single broadband connection – a real possibility. For instance, OFCOM (2007) suggests that 25Mbps would be sufficient to carry simultaneous multiple HDTV3 channels, broadband internet and voice services. Copper-based networks are investing in ADSL2+ deployment, which allows speeds up to 24Mbps. However, several factors such as the length, quality and dimensions of the copper cable and various other noise-contributing factors limit the overall availability of such speeds4. This suggests that offering triple play services through ADSL2+ may face significant limitations. There does not appear to exist, as of yet, a good definition of a NGA – such a definition

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Next Generation Access Networks and their Regulatory Implications

should, as expected, combine the various service characteristics (speed, symmetry, quality). OFCOM (2006a) defines next generation access as “broadband access services that are capable of delivering sustained bandwidths significantly in excess of those currently widely available using existing local access infrastructures or technologies” (p. 10). This definition merges two concepts: (i) the maximum bandwidth available (headline speed) and (ii) the continuous availability of current peak speeds (approx. 20Mbps) so as to allow triple play. A definition based solely on speed is probably not the most correct approach. It is important to note that in order to provide a sustainable bit rate, improvements in the upper layers of the network may be necessary. In fact, OFCOM (2007) raises the question as to whether the main short to medium term bottleneck may be the limitations of the backhaul network, which carries traffic from

the exchange to the core network and which is shared by all concurrent users. Therefore, in our opinion, and looking solely at telephone networks, the key element which differentiates current from next generation access networks is the type of infrastructure used. A NGA will in all likelihood depart from the current copper-based access network by making use of other technologies, such as fibre or wireless technologies. The deployment of fibre in the access network may be one of the following: Fibre to the Cabinet (FTTCab) or Fibre to the Home (FTTH)5. As we can see from Figure 1, with FTTCab subscribers continue to be connected through their copper loops, but fibre is deployed all the way to the street cabinet (partly replacing the copper loop), i.e. much closer to the subscriber. Such an architecture allows an operator to deploy DSLAMs at that location. Street cabinets increase their importance significantly in the access network,

Figure 1. NGA architectures Exchange

Street cabinet Copper

Copper

MDF

Fibre

CURRENT ACCESS NETWORK

ATU-R

DSLAM Street cabinet

Copper

SDF

Exchange

Fibre

MDF/ODF

Fibre

FTTCab-BASED NEXT GENERATION ACCESS NETWORK

ATU-R

DSLAM

Exchange Street cabinet Fibre ATU-R

50

Splitter

Fibre

ODF

Fibre

FTTH-BASED NEXT GENERATION ACCESS NETWORK (point-to-multipoint)

Next Generation Access Networks and their Regulatory Implications

in particular because they would then have active electronics in them. At the local exchange level, the Main Distribution Frame (MDF) may become superfluous, as the Sub-loop Distribution Frames (SDF) at the street cabinet level can take on their role in the network. FTTH implies the complete replacement of the copper loop by fibre and SDFs and MDFs are no longer necessary. Under this architecture, there are two possibilities. In a point-to-point architecture, each subscriber has a dedicated fibre connection. Such an architecture allows for virtually unlimited traffic speeds (OFCOM (2007)). In a point-to-multipoint architecture (also known as a Passive Optical Networks (PON)6), a single fibre serves multiple subscribers (e.g. 32 or 64). In that case, that fibre would be split (using a passive optical splitter) at some point between the exchange and the customer’s premises. This type of architecture would allow speeds of around 80Mbps per subscriber (with a 32 subscribers’ split) (OFCOM (2007)). The current access network sites, such as the local exchange and the street cabinets, would still be useful. The local exchanges would typically contain the Optical Distribution Frames (ODF) which terminate the fibre loops and the street cabinets could contain the passive optical splitters necessary for a pointto-multipoint FTTH architecture. If we look at the services which a NGA is likely to provide, there are already other networks capable of providing them, in particular, cable networks. The architecture of cable networks, typically hybrid fibre-coaxial (HFC) networks, is similar to an FTTCab deployment: fibre is deployed to a street cabinet level and coaxial cable is used to connect to each subscriber7. The current technology used is DOCSIS 2.0 and allows for speeds up to 50Mbps downstream and 30Mbps upstream, although the next version (DOCSIS 3.0) allows up to 220Mbps downstream and 120Mbps upstream (BSG (2007)). However, DOCSIS 3.0 entails investment in new head-end equipment and upgrades to customer premises equipment.

Our view is that a NGA will be more similar to the current cable architecture and, as such, a NGA based on cable is likely to be only a small upgrade from the current deployment, a view also shared by OFCOM (2007). This implies that the investment cable networks need to make to deploy a NGA is much smaller than that of copper-based access network owners (BSG (2007)). Wireless alternatives already exist (e.g. WiMAX8 and WiBro9) to reach subscriber’s homes. However, there is some degree of scepticism as to whether these are viable alternatives to wired broadband. BSG (2007), OFCOM (2006a) and OFCOM (2007) mention various problems such as coverage, contention, symmetry and speed which may not allow for triple play services to be provided by such wireless technologies. Additionally, and perhaps most importantly, spectrum availability may be an important and possibly insurmountable constraint. Therefore, in our opinion, such technologies are more likely to be a complement to a NGA rather than a substitute.

NGAs IN CONTEXT Value Chain and Firm’s Strategic Behaviour NGAs allow multiple services to be offered to consumers under different industry arrangements. The boundaries of a NGA operator are not clear yet. In short, NGAs allow functions to be separated in two different hierarchically ordered layers: the basic and media layers, comprising the transmission infrastructure; and the contents layer, encompassing communication and media services that can offered on such an infrastructure. Contrary to the PSTN architecture, where the network is tightly coupled with the (telephone) services it provides, a NGA is inherently a flexible platform for service delivery.

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Next Generation Access Networks and their Regulatory Implications

In a NGA, the service-related functions are independent from the underlying transport-related technologies, and this allows the uncoupling of service provision from transport. Thus, it is possible that users have access to a wide range of services from different service providers. The NGA value chain can be broken down horizontally and vertically. On the horizontal line, there are essentially three elements: customer equipment, network equipment, and interconnection with other networks. Vertically, as aforementioned, there are two layers: the service and the transport layer. It is on the vertical layer that most changes are expected to occur. The innovative separation of infrastructure from service allows firms to undertake new strategies, which means that the boundaries of the firm will be redesigned, as competitors fit into the value chain. The transport layer is no longer coupled with the service provided. The current division of the transport layer into access and core is likely to be challenged as the services provided do not impose the same constraints as under the PSTN architecture. Today, because most services are tightly coupled with the transport network, regulation has been applied to the bundle transport-services. NGAs allow regulation to be more service-neutral. Users are likely to combine different service providers and, as such, NGAs may have to support various contractual arrangements to meet consumers’ dynamic needs. In turn, this opens up opportunities for market players to operate in specific network elements and services. Broadly speaking, operators are likely to deploy NGAs where the gain from doing so outweighs the costs. In that context, there are several interesting questions which have to be raised and which are likely to influence NGA deployment decisions. Firstly, NGAs are costly and are likely to be deployed in densely populated areas or for new build premises, as the incremental cost is relatively small in those situations compared to

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current access technologies (OFCOM (2007)). For existing (or potential) customers, operators have two available strategies (and it is not clear yet which they will choose): NGAs could be rolled out in areas where customers already have the best possible access technologies, i.e. areas with short loops where ADSL already delivers high speeds; or NGAs could complement existing access technologies by delivering higher speeds for customers who currently have longer loops and cannot experience the best ADSL products. Secondly, NGA roll-out is more likely in countries where cable exerts a higher competitive pressure, i.e. telephone operators are likely to deploy NGAs in countries or regions where cable operators are trialling network upgrades which will allow them, in the future, to provide equivalent services to those of an NGA operator10; additionally, such a roll-out is also more likely where there is more to gain by selling additional (and currently unavailable) services such as IPTV11 (OFCOM (2007)). Thirdly, wholesale revenues are likely to see their importance increased for vertically integrated operators: the expected intensive downstream competition gives them an incentive to look more for wholesale revenues and thus try to recoup the investment made in NGAs (BSG (2007)). Fourthly, in some countries, the motivation for NGA deployment may be the gradual evolution of the network. For instance, Marcus and Elixmann (2008) argue that the deployment of a NGA in the Netherlands using FTTCab is the appropriate business strategy, although such an NGA will provide ADSL2+-type services (in terms of speed) because sub-loop lengths are still high. Fifthly, Amendola and Pupillo (2008), basing their assessment on JP Morgan (2006), put forward the idea that incumbents’ strategies regarding NGA deployment may be materially different from new entrants’ strategies. In particular, incumbents may prefer to choose FTTCab whereas new entrants may choose FTTH, bypassing the incumbent’s network. For incumbents, FTTCab

Next Generation Access Networks and their Regulatory Implications

allows the provision of improved or additional services which are likely to raise more revenue, at the same time as it may allow cost savings in operating expenditure: this a “gradual evolution” strategy which does not allow the provision of FTTH-like speeds and services, but which also does not imply significant investments. By contrast, provided new entrants have access to ducts in metropolitan areas – the main cost driver in NGA deployment –, as well as a sufficient market share, there may be a business case for FTTH deployment12.

Vertical Integration and Bottlenecks The advantages of vertically integrated NGAs are not clear cut. Operators may adopt a comprehensive approach ­ – encompassing both the infrastructure and service layers – or there could be specialization - different operators for the infrastructure and service layers. Theoretically, there may be a rationale for the regulator to interfere in the industry where there are bottlenecks. Considering that regulation is typically a second-best solution, the regulator should consider what incentives should be in place so as to permit innovation in both the infrastructure and services layers. In telecommunications, a bottleneck exists when it is not technically or economically feasible to duplicate some infrastructure elements. In the NGA case, the transport layer is at the core of the debate. The European Commission (2003) Recommendation identifies barriers to entry into a market (or the possibility of overcoming such barriers within a certain time period) as a key criteria to decide whether a market should or should not be susceptible to ex ante regulation, i.e. whether the market is an economic bottleneck. The existence of economies of scale, economies of scope and high sunk costs are commonly associated with barriers to entry. But, as the European Commission (2003) notes, barriers to entry may also be of a legal or

regulatory nature. As noted by Cave (2004), these types of barrier to entry can be non-strategic, i.e. they are not created by operators themselves. Economies of scale are usually associated with fixed costs. But as Schmalensee (2004) observes, economies of scale are not sufficient to allow incumbents to raise prices above cost without attracting entry; it is only when those costs are sunk13 that such a behaviour is to be expected. Undoubtedly, a NGA requires a substantial upfront investment by operators (BSG (2007), Williamson (2007)). Whether the transport layer of a NGA is likely to be a bottleneck depends on the “sunkness” of that investment. In much the same way as the traditional access network was regarded has a highly sunk investment (e.g. Pindyck (2007)), our view is that the investment in a NGA is largely sunk. As such, the transport layer of a NGA is likely to be an economic bottleneck, a point also made by the ERG (2007). On the issue of vertical integration, there is a concern that the operator controlling the bottleneck might enjoy a competitive advantage. If there are complementarities between the infrastructure and service layers (e.g. demand complementarities or economies of scope), vertical integration may be a sensible strategy and, as such, incumbents might want to keep any future developments in the infrastructure to themselves, claiming this is necessary to incentivise investment and innovation. On the other hand, new entrants view this development as a strategy for incumbents to reinforce their market power. As we have previously argued, a NGA will effectively allow a more clear-cut separation between the infrastructure and service layers, which suggests that these two layers will enjoy fewer complementarities than they did thus far. This leads us to conclude that the concept of bottleneck in NGAs is likely to be dynamic. If the transport and service layers become more separate, telecom operators are likely to develop independent strategies for each of these. For example, contrary to the PSTN, full control of

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Next Generation Access Networks and their Regulatory Implications

a given communication network to provide the service to final consumers might not be needed or even desirable. Indeed, as interconnection on a NGA is facilitated, it is quite likely that, under certain circumstances, multiple alternative platforms and protocols exist, which allow an operator to choose the most suitable connection for a given client. Thus, the technological innovation and the interconnection development might sweep aside the traditional response to bottlenecks. This layer separation challenges the current regulatory environment, as it allows regulators to be more service-neutral, focusing instead on guaranteeing access to the infrastructure while allowing competition on the service level.

The European Regulatory Framework The European Regulatory Framework (ERF)14 regulates electronic communication services in Europe. The rationale of the regulatory approach is to make telecommunications markets more competitive, so that as dominant operators see their market power reduced, reliance on competition rules will increase while sector-specific regulation is gradually phased out. Regulatory obligations are imposed in three steps: firstly, markets susceptible to ex ante regulation are defined; secondly, “significant market power” (SMP) operators are identified in those markets; and finally, regulatory obligations are imposed on the SMP operators. Markets susceptible to ex ante regulation are those where there are significant barriers to entry which are unlikely to be overcome within a relevant time horizon and where competition law alone is unlikely to solve the problem. In this context, the European Commission (2003) adopted a Recommendation (amended by the European Commission (2007b) Recommendation) that defined the product and service markets susceptible to ex ante regulation.

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The regulatory obligations, which can be imposed on SMP operators are: transparency; non-discrimination, accounting separation, compulsory access, and cost orientation as well as any other obligations in exceptional circumstances. Under its amendment to the ERF (European Commission (2007a)), functional separation may also be imposed. The underlying rationale of the ERF is based on the ladder of investment principle (see, for example, Cave (2006) or ERG (2007)). The regulatory regime is designed to encourage investment by both incumbents and new entrants. As for the latter, the significant necessary investments to provide telecommunications services are unlikely to be made on a one-off basis. What is likely to happen is that new entrants enter the market slowly and invest in capital assets gradually, as their customer base also increases. But in order to do so they need to be able to provide services at a time where their networks are not yet fully built and hence may require several complementary services from incumbents. As new entrants climb the “ladder of investment”, they slowly reach final customers with their own networks, competing directly and on several dimensions (e.g. price, quality, coverage, etc) with incumbents. In effect, as the ERG (2004) points out, “... such interventions have as their long-term objective the emergence of self-sustaining effective competition and the ultimate withdrawal of regulatory obligations” (p. 68). In essence, the ultimate aim of the regulatory framework is to promote network competition.15 Until such effective network competition materialises, the ERF is a “substitute”. As such, it tries to emulate what would happen under true network competition. The underlying idea of promoting competition at the deepest possible level in the network is an attempt to give new entrants as much flexibility as possible in the design (characteristics, price, quality, etc) of the services they sell to final customers.

Next Generation Access Networks and their Regulatory Implications

Wholesale Markets Market definition, which has both a product and geographic dimension, starts from end-user demands (retail markets); network or wholesale inputs are a derived demand. Hence, if two services provided over different platforms are in the same market, then inputs into those services (e.g. wholesale products) would also belong to the same market. Broadly speaking, there are three types of wholesale services which are likely to be provided over a NGA: existing services, better quality versions of existing services and new services (OFCOM (2006a)). There is, however, considerable uncertainty as to what these services may actually be in the future. For existing services, it could be argued that although the technology used to deliver them over a NGA is different, the services themselves are the same and, as such, will belong to the same market as they do today. Better quality services may belong to the same market as current wholesale services if they are substitutable (price constrained). Finally, new services unique to NGAs may belong to a separate market. For instance, Cave et al (2006) note that a fibre-based network will not only allow the provision of the same services provided today, but also of new services such as IPTV. In that case, a separate wholesale market would also need to be defined, which could be considered as “emerging” and hence not subject to ex ante regulation. But this input may also be used as an input for other retail services (such as those mentioned previously), which raises the question of whether the new services are sufficiently important for this to be a separate market. A NGA will affect essentially two markets contained in the European Commission (2003) Recommendation: the market for wholesale unbundled access (including shared access) to metallic loops and sub-loops (market 11) and the market for wholesale broadband access (market 12). The European Commission (2007b) Recom-

mendation replaces the 2003 Recommendation and maintains these two markets as markets susceptible to ex ante regulation. However, and following the arguments put forward by the ERG (2007) and Cave et al (2006) (among others), the first market is now the market for wholesale (physical) network infrastructure access (including shared or fully unbundled access) at a fixed location. The second market (wholesale broadband access) maintains its designation. ERG (2007) argued that the European Commission (2003) definition of market 11 excluded fibre access by focusing solely on metallic loops and would thus have to be enlarged. Such a definition should be sufficiently broad so as to include the most likely network layouts under discussion: FTTCab (where local loops would still be partly copper-based) and FTTH (where loops would be completely fibre-based). As OFCOM (2006b) noted when conducting its wholesale local access review, although copper and cable local access services belonged to the same market (i.e. fibre access was excluded), that does not mean that a NGA based on fibre would not be subject to ex ante regulation – after deployment, a new market review needs to be carried out so as to analyse the inclusion/exclusion of fibre access in the relevant local access market. As for market 12, the ERG (2007) argued that the European Commission (2003) definition included the provision of wholesale access services between the customer’s premises and the DSLAM or higher levels of the IP network and this would be broadly maintained under a FTTCab or FTTH architecture. As such, the deployment of NGAs would not affect the definition of this market. Geographic market definition, however, is very likely to change significantly with the emergence of NGAs. Geographic markets are defined where there is some homogeneity in the competitive conditions within that market. Therefore, several neighbouring geographic markets may exist, in which case the competitive conditions must be similar within the market but clearly different

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Next Generation Access Networks and their Regulatory Implications

across markets (see, for example, European Commission (1997, 2002)). Competitive conditions refer, among other things, to possible differences in the costs of providing the service or existing or potential competition (namely the presence of cable providers) (Amendola and Pupillo (2008) and BSG (2007)). On the cost side, it is likely that there are joint and/or common costs to serving neighbourhoods or even cities16. On the competition side, it is quite possible that some geographic markets will experience strong network competition due to the presence of cable providers whilst others may have less or no network competition at all (BSG (2007)). Regulators are well aware of this. The key aspect of OFCOM’s (2006b) review was the introduction of geographic wholesale markets, based on competitive local conditions, an approach also followed by CMT (2007) (the Spanish regulator). In particular, OFCOM (2006b) concluded that internet provision through cable networks was in the same retail and wholesale market as ADSL broadband internet access – even though cable and ADSL broadband are provided over different networks, they exert sufficient competitive pressure on each other to belong to the same product market. From a geographic point of view, OFCOM (2006b) sought to identify markets where competitive conditions were relatively homogeneous: the main competitive factors identified were the availability of cable-based services, the current or planned availability of local loop unbundling (LLU)-based services or the likelihood of LLUbased entry, as well as the existence of common pricing constraints. Market power was then assessed in each of these geographic markets and the imposition (or not) of regulatory remedies could well differ between markets as pointed out by Amendola and Pupillo (2008), BSG (2007) and Waverman and Dasgupta (2006).

REGULATORY CHALLENGES OF NGAs Regulatory Approaches to NGAs OFCOM (2006a) reiterates that the promotion of competition at the deepest possible level in the network is expected to lead to a “ladder of investment”. If the same principle is applied to NGAs, then there would be various levels where competition may materialise: •

•

•

•

Ducts and trenches: The ability to use the incumbent’s ducts and trenches to roll out a NGA significantly reduces deployment costs and allows operators a choice of different technological solutions for service provision; Sub-loop unbundling: This would be equivalent to local loop unbundling, but would occur at the cabinet (closer to the customer); this option has various problems, because it requires other operators to invest significantly in order to move closer to the customer, thus requiring a higher market share to compensate for such an investment; in addition, there may be space constraints at the cabinet level; Gibre unbundling at the exchange: This is only possible with point-to-point fibre; in addition, operators may find it worth investing only if part of that investment is offset by the sale of exchanges (which would no longer be necessary); Wholesale bitstream products: If competition deeper in the network is not expected to deliver benefits, offering wholesale interconnection products may be a good alternative, although at the cost of less innovation in NGA services.

According to the ERG (2007), the possibility of unbundling at the physical layer depends crucially

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Next Generation Access Networks and their Regulatory Implications

on the NGA layout. With FTTCab, unbundling of local loops would be possible in the same way as it is today, but closer to the customer – in street cabinets. However, Marcus and Elixmann (2008) argue that with FTTCab the standard regulatory remedies are harder to apply because of the geographic dispersion of street cabinets (which become the points of interconnection) as well as the likely restrictions in terms of access and space these have. Even when it is possible to unbundle at the street cabinet level, there is a problem of market size. The first mover – i.e. the operator that sets up FTTCab first – might have an advantage if the market is not large enough to accommodate more than one operator and competition would thus be compromised. In addition, and according to the ERG (2007), it is important to consider the need for a backhaul between the street cabinet and other operators’ networks, which raises the possibility of implementing duct sharing. The change in infrastructure may affect LLU, because MDFs will be reconfigured or even phased-out. There must be a balance between the freedom of operators to roll-out NGAs and the need for promoting competition. The worry is that NGAs have significant economies of scale, economies of scope with incumbents’ facilities and few access alternatives (e.g. wireless)17. For FTTH deployment, construction costs make up the majority of the investment necessary. As such, duct sharing could be imposed on a symmetric basis on all operators. With FTTH, the unbundling possibilities depend on the architecture chosen: if a point-to-point solution is adopted, it is possible to unbundle fibre loops in much the same way as copper loops; if a pointto-multipoint solution is adopted, then a natural unbundling frontier would be at the passive optical splitter level (ERG (2007)). Following OFCOM (2006a), the regulatory mechanisms commonly used are: •

Mandatory and non-discriminatory access but no price regulation

• • • •

Retail-minus prices Cost-based prices Cost-based prices with activity-specific cost of capital Adjusted returns

Imposing mandatory and non-discriminatory access but abstaining from regulating prices would allow operators to decide whether to invest on NGA depending on their expected returns from the investment. Such an approach, however, tilts the balance in favour of vertically-integrated incumbents who can still distort competition in their favour, either through high prices for access, cross-subsidies to the downstream division or margin squeeze competitors (OFCOM (2006a)). Such a strategy by the vertically integrated operator would have the objective of foreclosing the retail market and result in a monopoly situation. Retail-minus (wholesale) prices are based on retail prices less the necessary retail margin for other operators to supply the service profitably. Such a pricing mechanism is normally used when (wholesale) competition is expected to emerge in the future, thus driving wholesale prices towards costs, or for new and innovative markets. Provided there is no margin squeeze, retail-minus prices is likely to result in efficient investment, as there is no cap to investor returns. Cost-based prices are usually calculated using Long-Run Incremental Cost (LRIC) principles, and thus reflect the replacement cost of the assets used by a given service, including a (companylevel) cost of capital which reflects the associated risk. By contrast, in specific cases where there is a higher or lower systematic risk (which cannot be diversified), an activity-specific cost of capital may be used. When prices are regulated, the investor faces asymmetric returns as he is allowed to earn a predetermined (regulated) return if the investment is successful, but has to support all the losses if it is not. This results in reduced incentives to invest which may be corrected through

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Next Generation Access Networks and their Regulatory Implications

prices which adjust returns for this asymmetry (OFCOM (2006a))18. The migration from existing regulation must consider the investment made by competitors, whether that investment was recouped and whether such competitors will continue to have access to wholesale products equivalent or better than the current ones. A balance between costs savings coming from the NGA and eventual risks to competition must also be struck. As mentioned earlier, a NGA will continue to be an input to existing services as well as a means to deliver entirely new services. In terms of regulatory remedies, this raises the possibility of mandated access but only up to certain speeds (the existing services) (Cave et al (2006)). Williamson (2007) puts forward the argument that anchor product regulation – the creation of equivalent products to those existing today, but delivered through the NGA - is a reasonable regulatory remedy for the problems raised by a NGA. As proposed by Williamson (2007) and OFCOM (2007), anchor product regulation is a mix of the two extreme regulatory solutions: price regulation and forbearance. On the one hand, it protects consumers and other operators by requiring the offer of equivalent services through the NGA, possibly at regulated prices, to those existing today; on the other hand, it leaves the NGA owner with sufficient flexibility regarding the price and product characteristics for the new services a NGA will allow. Needless to say, the existence of anchor products would in itself constrain the pricing of the new services if they are in some way substitutable. Blum et al (2007) show that the regulatory threat of intervention may be sufficient to prevent an operator from charging too high a price. This is particularly relevant in the light of the German case of allowing a regulatory holiday on operators deploying NGAs. The regulator can influence both the likelihood of NGA investment as well as their respective prices even without imposing price regulation.

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Interestingly, NGAs make forbearance a more viable alternative (provided, of course, access is provided on a non-discriminatory and equivalent basis to all third parties), as the NGA owner will want to recoup its investment and hence carry as much traffic as possible, even if such traffic belongs to rival operators (OFCOM (2007) and BSG (2007)). Partly, the regulatory problem presented by NGAs verges on what is likely to happen regarding the voluntary provision of wholesale access products. If the NGA owner decides to create a wholesale product so as to recoup its investment, then there may be no need for regulatory intervention. The issue is similar to the incentives faced by mobile operators to allow the creation of mobile virtual network operators (MVNOs): in that case, the creation of the wholesale product was almost never a natural market outcome and had to be mandated. The case of cable is similar: such a wholesale product does not exist (although no mandated access has been determined in virtually all countries). We conjecture that initially the NGA owner will be reluctant to create a wholesale product which would allow competitors to access potential retail customers. However, after some time has elapsed and the NGA owner has already gained a sufficient customer base, it is unlikely that the current offer (product characteristics, prices, etc) will attract further customers. This is normally the phase where product differentiation/market segmentation becomes attractive. The NGA owner can himself create such differentiated products to increase penetration (much in the same way as mobile operators did by creating “secondary brands” using the same network) or create a wholesale product and allow other operators to carry out that task. The underlying assumption is that downstream variety increases upstream demand and this variety is better provided by multiple firms19. In turn, if this line of thought materialises, a regulatory holiday such as that suggested in

Next Generation Access Networks and their Regulatory Implications

Germany may be the best regulatory strategy. After that regulatory holiday, it may not even be necessary for the regulator to mandate access (or to announce at the outset that it will mandate access after the regulatory holiday): regulatory threat has worked before (e.g. on BT in the UK) and the incumbent created such a product even in the absence of “actual” regulation. This suggests that regulators should, at this point, provide clear policy indications of what they are likely to do (and why) once the NGA has been deployed.

Is Moving up the Ladder Necessarily Bad? Even if a NGA is a bottleneck, this does not necessarily imply the existence of less competition, but rather of a different type of competition (Williamson (2007)). For instance, switching service providers may become easier, faults associated with local loop unbundling may become less likely and entry may occur in the markets for services and applications which a NGA will allow. The design of the NGA described by Openreach (2007a, 2007b) suggests that this may indeed be so. Openreach (2007a) is consulting on the deployment of FTTH using a point-to-multipoint architecture. The equipment at the customer’s premises would support up to two service providers, one for voice and one for data20. Thus, and although the ladder of investment principle is still appropriate to deal with enduring economic bottlenecks, with NGAs we are likely to see a move up the ladder, i.e. the deepest level in the network where competition will be promoted may not be as “deep” as it is today. In particular, we may see a move away from promoting competition at the physical layer towards competition in upper (service) layers (e.g. moving away from ULL towards wholesale broadband access). This is particularly so if MDFs are gradually phased-out. In that case, a stronger focus on wholesale broadband access is likely to materialise, as regulators will push for a design of such products which emulates

as much as possible the choices operators could make if competition could take place at a deeper (e.g. physical) level in the network. In fact, OFCOM (2007) suggests that NGA deployment is likely to shift regulation from passive input regulation (such as duct, copper lines or optical fibre) to active input regulation (equipment such as DSLAMs or Optical Line Terminals), as the viability and effectiveness of passive input regulation is likely to be reduced. OFCOM (2007) discusses the limitations of passive input competition as network deployment moves away from densely populated areas. In such areas, it may be more appealing to use active input products. Provided such active input products are configurable in as close a way as possible to what another operator could achieve with passive inputs, the benefits of competition are likely to emerge without the associated costs of passive input use21.

The Investment/Competition Dilemma OFCOM (2006a) suggests that if NGAs are a bottleneck, then regulators today would face a serious problem. The usual remedies for such markets, such as mandated access and regulated prices (cost-based prices, retail-minus or any other approach), would reduce investor returns. NGAs cause a regulatory dilemma (Laffont and Tirole (2001)): regulation designed to promote competition after network deployment (such as mandated access and regulated prices) will reduce the incentives to invest in the first place; if the regulatory approach wishes to promote investment, then this is likely to be coupled with reduced competition after network deployment. This problem makes it important to clarify the regulatory approach to be followed after network deployment before the investment takes place. Gayle and Weisman (2007) discuss the tradeoffs between static and dynamic efficiency. In particular, an analogy is made with policies re-

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Next Generation Access Networks and their Regulatory Implications

garding copyrights, patents and trademarks, where distortions to static efficiency are accepted (e.g. prices above marginal costs) so as to encourage dynamic efficiency through investment in innovation. Gayle and Weisman (2007) argue that when unbundled network elements are price regulated, incumbent have less incentives to invest and hence dynamic efficiency is sacrificed. Jung et al (2008) find some empirical support for this claim. Pindyck (2007) argues that mandatory unbundling at cost-based prices discourages investment by incumbents and new entrants, as the adoption of current cost principles in a market which is permanently faced with a decreasing price trend does not allow the investor to recoup its investment. As Hausman (1997) points out, the dynamic effects of regulation are often much larger than the static effects of monopoly power and hence the regulator should err on the side of leniency to encourage new products22. NGA roll-out is expected to have significant risks. Under regulation, this risk is likely to be shared between the operators and consumers: consumers would support all the risk if operators could freely define prices and operators would support most of the risk if prices were regulatory constrained to reflect costs. Here we have a dilemma: if operators were free to set prices, one would expect a relatively quick NGA roll-out, which would deliver dynamic efficiency at the cost of allocative efficiency (operators would charge prices in excess of costs and extract consumer surplus). By contrast, a cost-based price is likely to reduce incentives for NGA deployment, as the returns to investment are capped above but not below (OFCOM (2007)). Even if only mandated access to NGAs is imposed, Waverman and Dasgupta (2006) stress that this may reduce both incumbents’ and new entrants’ incentives to invest in their deployment. On this relationship between investment and the regulatory regime, BSG (2007) notes that where network competition is considered to be sufficiently intense, such as in the USA, Canada

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and Hong Kong, regulators have adopted a liberal approach and not required network owners to provide access to other operators. Naturally, such an approach has a positive effect on investment incentives. In particular, in Canada, a Regulatory Review Panel concluded that unbundling based on the ladder of investment principle could undermine the achievement of genuine network competition. In the Netherlands and Belgium, where cable competition is strong, regulators are considering whether to impose regulatory obligations on operators deploying NGAs. The US regulatory approach is based on permanent forbearance, i.e. there is no regulatory requirement for the network owner to provide access to third parties. Such an approach has the great merit of delivering the right investment incentives, making the investor fully liable to potential losses but also allowing him to retain any gains obtained. Forbearance could also be temporary, where the regulator explicitly abstains from regulating services for a given period of time (e.g. the case of Germany for the roll-out of NGAs). This would be similar to the patent regime. The success of forbearance as a regulatory approach depends on the likelihood of network competition: if network competition is unlikely to materialise, then any type of forbearance will distort the market: prices will be higher than socially optimal (allocative inefficiency) and there may be over-investment. If network competition is expected to emerge after a given period of time, then temporary forbearance may give the NGA owner sufficient assurances to invest in the first place.

CONCLUSION The introduction of NGAs is likely to reshape the telecommunications sector. Whilst the NGA infrastructure is likely to be a bottleneck and, thus, attract regulatory scrutiny, service operation is likely to be more infrastructure-independent

Next Generation Access Networks and their Regulatory Implications

and, as such, raise questions as to the desirability of the vertically integrated incumbent operator model. There is, however, substantial uncertainty as to how the market will evolve. This suggests that regulators should thread carefully. In particular, the ladder of investment principle is likely to be affected by NGAs, but this is not necessarily bad from a competition point of view. Moreover, the fact that NGAs are yet to be deployed raises the investment/competition dilemma: if regulators impose (or threaten to impose) regulatory remedies after NGA roll-out, this will obviously affect incentives to deploy such networks in the first place. Whilst it is desirable to promote competition in any sector (static efficiency), substantial benefits often accrue from investment in innovations (dynamic efficiency). This trade-off is at the heart of the discussion of the regulatory challenges raised by NGAs.

REFERENCES Amendola, G. B., & Pupillo, L. M. (2008). The Economics of Next Generation Access Networks and Regulatory Governance: Towards Geographic Patterns of Regulation. Communications & Strategies, 69, 85-105. Blum, U., Growitsch, C., & Krap, N. (2007). Broadband Investment and the Threat of Regulation: Preventing Monopoly Exploitation or Infrastructure Construction? Review of Network Economics, 6(3), 342-354. Broadband Stakeholder Group (BSG). (2007). Pipe Dreams? Prospects for next generation broadband deployment in the UK. London: BSG. Cave, M. (2006). Encouraging network competition via the ladder of investment, Telecommunications Policy, 30, 223-237. Cave, M., Stumpf, U., & Valletti, T. (2006). A Review of certain markets included in the

Commission’s Recommendation on Relevant Markets subject to ex ante Regulation. Report for the European Commission. Cave, M. (2004). Economic Aspects of the New Regulatory Regime for Electronic Communications Services. In P. Buiges & P. Rey (Eds), The Economics of Antitrust and Regulation in Telecommunications (pp. 27-41). E. Elgar. Comisión del Mercado de las Telecomunicaciones (CMT). (2007). Consulta publica sobre redes de acceso de nueva generacion. European Regulators Group (ERG). (2007). ERG Consultation Document on Regulatory Principles of NGA, ERG (07) 16. European Regulators Group (ERG). (2004). ERG common position on the approach to appropriate remedies in the New Regulatory Framework. ERG 30(03). European Commission. (2007a). Proposal for a directive of the European Parliament and of the Council amending Directives 2002/21/EC on a common regulatory framework for electronic communications networks and services, 2002/19/EC on access to, and interconnection of, electronic communications networks and services, and 2002/20/EC on the authorisation of electronic communications networks and services. European Commission (2007b). Recommendation 2007/879/EC of 17 December 2007 on relevant product and service markets within the electronic communications sector susceptible to ex ante regulation in accordance with Directive 2002/21/EC of the European Parliament and of the Council on a common regulatory framework for electronic communications networks and services. OJEU, L344/65. European Commission (2003). Recommendation 2003/311 of 11 February 2003 on relevant product and service markets within the electronic communications sector susceptible to ex ante regula-

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Next Generation Access Networks and their Regulatory Implications

tion in accordance with Directive 2002/21/EC of the European Parliament and of the Council on a common regulatory framework for electronic communications networks and services. OJEC, L 114/45. European Commission (2002). Guidelines 2002/C 165/03 on market analysis and the assessment of significant market power under the Community regulatory framework for electronic communications networks and services. OJEC, C165/31. European Commission (1997). Notice on the definition of the relevant market for the purposes of Community competition law. OJEC, C 372. Gayle, P., & Weisman, D. (2007). Efficiency Trade-Offs in the Design of Competition Policy for the Telecommunications Industry. Review of Network Economics, 6(3), 321-341. Hausman, J. (1997). Valuing the effect of regulation on new services in telecommunications. Brookings Papers on Economic Activity, Microeconomics, 28(1), 1-54. JP Morgan (2006). The fibre battle. Jung, I., Gayle, P., & Lehman, D. (2008). Competition and investment in telecommunications. Applied Economics, 40, 303-313. Laffont, J. J., & Tirole, J. (2001). Competition in Telecommunications. MIT Press. Marcus, J. S., & Elixmann, D. (2008). Regulatory Approaches to Next Generation Networks (NGNs): An International Comparison. Communications & Strategies, 69, 19-40. OFCOM (2007). Future broadband policy approach to next generation access. Public consultation document. OFCOM (2006a). Regulatory challenges posed by next generation access networks. Public discussion document.

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OFCOM (2006b). Review of the wholesale broadband access markets 2006/07. Public consultation document. Openreach (2007a). Openreach services delivered over Fibre To The Premises (FTTP). Consultation document. Openreach (2007b). Product definition overview: Generic Ethernet Access delivered over Fibre to the Premises. Pindyck, R. (2007). Mandatory Unbundling and Irreversible Investment in Telecom Networks. Review of Network Economics, 6(3), 274-298. Schmalensee, R. (2004). Sunk Costs and Antitrust Barriers to Entry. American Economic Review, 94(2), 471-475. Waverman, L., & Dasgupta, K. (2006). Investment in telecommunication networks: A 21st Century perspective. Unpublished manuscript. Williamson, B. (2007, March). Risk, reward and efficient investment in access networks. Paper presented at an OFCOM European seminar on regulatory challenges posed by next generation access networks, London, United Kindgom.

KeY terms ADSL: ADSL (Asymmetric Digital Subscriber Line) allows voice and data to be sent simultaneously over the existing copper-based telephone line (ITU-T Recommendation G.992.1), with speeds up to 6Mbps downstream and 640Kbps upstream. In July 2002, the ITU completed G.992.3 and G.992.4, two new standards for ADSL technology collectively called “ADSL2”, allowing for a maximum 12Mbps downstream speed and 1.3Mbps upstream. In January 2003, a new standard called ADSL2+ (ITU G.992.5) doubled the bandwidth used for downstream

Next Generation Access Networks and their Regulatory Implications

data transmission, achieving rates of 20 Mbps on phone lines as long at 1,5Km. FTTCab: FTTCab (Fibre-to-the-Cabinet) is a network architecture where optical fibre replaces copper in the access network connection between the local exchange and street cabinets. FTTH: FTTH (Fibre-to-the-Home) is a network architecture which makes use of optical fibre to connect to the subscriber’s homes. IPTV: IPTV (Internet Protocol Television) is a digital television service delivered through a broadband connection.

Mbps range, over short distances, usually between 300 and 1500 meters, using twisted pair copper wire. The shorter is the distance, the faster the connection rate. VDSL2 (ITU-T G.993.2) allows speeds up to 100Mbps each way, but depends crucially on the length and quality of the copper loop. For loops longer than approximately 1.6Km it no longer provides a faster bit rate than ADSL2+.

EnDNOTES

1

Ladder of Investment Principle: Regulatory principle with the objective of encouraging investment by both incumbents and new entrants and ultimately promoting network competition. It is based on the idea that investments by new entrants are gradual as their customer base increases, but until this happens several complementary services (provided by incumbents) are needed.



2

Next Generation Access Network (NGA): Not fully copper-based access network, capable of providing broadband access services with sustained bandwidths clearly higher than those available with fully copper-based access networks.

3

Next Generation Network (NGN): A multiservice (voice, data, video, etc) packet-based network in which service-related functions are independent from the underlying transport-related technologies. NGA Layers: The basic and media layers comprise the transmission infrastructure and the contents layer encompasses the communication and media services that can offered on such an infrastructure.



4

5

6

Triple Play: Provision of three communications services (voice, data and television) over a single broadband connection. VDSL: VDSL (very high speed digital subscriber line) download speeds are in the 13-55



HDSL (high-data-rate digital subscriber line) delivers 1.544 Mbps of bandwidth each way over two copper twisted pairs. The operating range of HDSL is limited to approximately 3,5Km. SDSL (single-line digital subscriber line) delivers 1.544 Mbps both downstream and upstream over a single copper twisted pair. The use of a single twisted pair limits the operating range of SDSL to approximately 3Km. This type of service uses all the bandwidth available and, therefore, does not allow the telephone service to be provided simultaneously. High-definition television (HDTV) is a digital television broadcasting system with a greater screen resolution than traditional systems. For instance, in the UK only about 50% of households will be able to access 8Mbps or more (BSG (2007)). There are other possibilities, such as Fibre to the Building (FTTB); the key difference in all variants is the end-point of the fibre (cabinet, building, home). Different PON systems exist: Broadband PON (BPON), Gigabit PON (GPON) and Ethernet PON (EPON). EPON makes use of an Ethernet router at the street level instead of a passive optical splitter.

63

Next Generation Access Networks and their Regulatory Implications

7



8



9



10



11



12

13

14







64

Contention is a well known problem for cable networks as subscribers have to share the available capacity at the street cabinet level. Worldwide Interoperability for Microwave Access (WiMAX) is based on the IEEE 802.16 standard. According to the WiMAX Forum, “WiMAX provides fixed , nomadic, portable and, soon, mobile wireless broadband connectivity without the need for direct line-of-sight with a base station. In a typical cell radius deployment of three to ten kilometers, WiMAX Forum Certified™ systems can be expected to deliver capacity of up to 40 Mbps per channel, for fixed and portable access applications.” WiBro (Wireless Broadband) is based on the same standard as WiMAX (802.16), but adapted to provide connectivity on the move (such as that required by mobile phone access). The rationale for NGA deployment in such a scenario is the “first mover advantage” that telephone operators would enjoy. IPTV (Internet Protocol Television) is a digital television service delivered through a broadband connection. Amendola and Pupillo (2008) mention two such examples: Iliad in France and NetCologne in Germany. Sunk costs are costs which cannot be avoided if a firm stops producing, i.e. they are not recoverable. They are usually associated with specific assets which have little or no alternative use in other activities. The European Regulatory Framework includes Directive 2002/21/EC (“Framework

15



16

18 17

19



20

21



22



Directive”), Directive 2002/20/EC (“Authorisation Directive”), Directive 2002/19/EC (“Access Directive”), Directive 2002/22/EC (“Universal Service Directive”), Directive 2002/58/EC (“Data Protection Directive”) and Directive 2002/77/EC (“Competition Directive”). The European Commission is currently consulting on a proposal to amend the ERF (European Commission (2007a)). It should be noted that this theory largely proved to be a failure in the United States, following the Telecommunications Act 1996: there is little evidence that the unbundling and resale regimes were used temporarily while new entrants built their networks. We thank a referee for pointing this out. We thank a referee for pointing this out. We thank a referee for this observation. This type of pricing, suggested by OFCOM (2006a), could take the form of a glide path from higher/lower expected returns towards the expected returns. When returns are higher than expected, the glide path would allow the operator to keep a proportion of those returns for a longer period. We thank a referee for this observation. Openreach is not considering the deployment of copper-based services to such customers nor any variant of LLU or wholesale line rental. OFCOM (2007) proposes the creation of such active line Ethernet-based access products both for FTTH and FTTCab deployments (although sub-loop unbundling, a passive input product, is also suggested). We thank a referee for this observation.

65

Chapter V

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry Carol C. McDonough University of Massachusetts Lowell, USA

Abstract The United States’ wireless telephone industry has evolved from a minor segment of the communications industry to a major provider of voice, and increasingly data and video communication. The industry uses radiowaves to transmit signals, and radiowave spectrum is regulated by the federal government. Moreover, local transmission requires unobstructed antennae, which in rural and suburban areas has led to the construction of wireless towers. States and municipalities have sought to regulate the construction of such towers, citing issues of aesthetics and health. The development of the wireless industry has been constrained by such government regulation. This chapter discusses the impact of government on the market structure of the wireless industry.

Introduction Wireless telephony has evolved from a minor component of the telephony industry to a ubiquitous component today. In the developing world, wireless communication provides access to telephony services without the cost of building out landline infrastructures. Mobile phone penetration rates, which measure the number of mobile phones

per 100 population, are high in industrialized nations and lower in less developed areas. (Table 1). These numbers often reflect multiple phones per wireless subscriber. Governments, at the federal, state, and local levels, have had a major impact on the structure of the wireless industry, through policies on licensing, mergers/acquisitions, pricing, and tower construction. This chapter discusses the impact

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Table 1. 2007 Mobile phone penetration rates Luxembourg

158%

Hong Kong

140%

Western Europe

110%

Europe total

95%

United States

85%

China

50%

India

non-Government users. The National Telecommunications and Information Administration (NTIA) manages frequencies to departments and agencies of the U.S. Government. Table 2 details information on the allocation of RF spectrum in the United States. In the United States in the 1970’s, the FCC planned to license a single cellular system in each area, operated by the local wireline phone company. Experimental wireless licenses were granted in several areas. In some European countries, government-owned telephone companies, known as Post, Telephone, and Telegraph (PTT) companies, provided early wireless service. In 1981, the FCC altered the cellular structure to a duopoly. 50 MHz of spectrum in the 800 MHz frequency band were set aside for two competing systems in each market, one for the local wireline telephone company and the other for a nonwireline company. In each of 734 cellular markets (306 Metropolitan Statistical Areas (MSA) and 428 Rural Service Areas (RSA)), the FCC used non-revenue generating processes such as comparative hearings and lotteries to select a nonwireline company. The FCC started to license cellular companies in 1982 and had essentially completed the licensing process by 1991.2 Similarly, the wireless industry in Canada, regulated by Industry Canada, expanded to two cellular telephone carriers in 1984. 3 Another earlier form of mobile telephony is enhanced specialized mobile radio (ESMR), developed by assembling frequency bands originally allocated for two-way dispatch services. In the United States, ESMR operates in the 800MHz

23%

Worldwide 

13%

Sources: BBC News,11/07; Informa,2007; Wikipedia; Fortune, 5/26/08

of U.S. government policies on the structure of the U.S. wireless telephony industry.

Early history of the wireless industry Because wireless telephony uses radio wavelengths for transmission, government regulation and distribution of wavelength affects competition in the industry. Internationally, the radio frequency (RF) spectrum is allocated by the International Telecommunication Union (ITU). Governments globally have taken on the assigning of frequencies, and this can be a highly political decision.1 Within the United States and its possessions, the RF spectrum is further allocated to non-Government and Government users. The Federal Communications Commission (FCC), acting under the authority of Congress, allocates frequencies to

Table 2. Allocation of radio spectrum in the United States 30 km |

VLF | 10 kHz

66

3 km |

LF

300 m |

MF | 100 kHz

30 m |

HF | 1 MHz

3 m |

VHF | 10 MHz

| 100 MHz

30 cm |

UHF | 1 GHz

3 cm |

SHF | 10 GHz

3 mm |

EHF | 100 GHz

Infrared

Visible Light

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

range with 14 MHz of spectrum space. There usually is one ESMR service provider in a geographic area.

The demand for wireless telephony increases By the 1990s, as technological advances introduced digital technology to the industry, the demand for wireless services had grown significantly. A developing literature advocated for the use of competitive bidding to assign wireless licenses. Early contributors to the literature on auctions as an efficient way to distribute resources in the public domain to promote social welfare included Herzel and Coase.4 The argument for using the price system to allocate wireless spectrum was based on three types of efficiencies: elimination of rent dissipation associated with comparative hearings; assignment of licenses to the most productive suppliers, saving the transaction costs of secondary market redistributions; and the generation of revenues for public use.5 Competitive bidding was adopted by New Zealand in 1989, India in 1991 and the United States in 1993. At least twenty-five other countries have instituted license auctions in recent years.

The role of the United States’ government in determining industry structure: PCS auction structure6 In 1993, Congress authorized the FCC to auction off broadband PCS licenses to operate in the 2 GHz band of the spectrum. PCS spectrum almost quadrupled the total amount of spectrum allocated to wireless service. The FCC divided PCS spectrum into six frequency blocks (A-F), creating the potential for a maximum of six additional wireless providers per

market. The wireless market was subdivided into 51 large blocks known as Major Trading Areas (MTA), and further subdivided into 493 smaller blocks known as Basic Trading Areas (BTA’s). Blocks C and F were designated as entrepreneurial blocks, with upper limits set on bidders’ gross revenues and total assets. Table 3 shows the PCS auction structure. Each auction was conducted using the simultaneous multiple round auction process. Multiple round auctions provide more information to bidders about the value that other bidders place on the licenses. The likelihood that the licenses are acquired by those who value them most highly is increased, and greater revenue is gained. Simultaneous auctions are preferable to sequential auctions: simultaneous auctions increase the value of licenses by facilitating efficient aggregation and, by providing more information on the value of interdependent licenses, reduce the propensity of sophisticated bidders to bid cautiously to avoid the winner’s curse7. Although the purpose of distributing PCS licenses via simultaneous multiple round auctions was to place the licenses in their most highly valued use, concerns arose that there were insufficient safeguards against reflexive bidding8 and speculative bidding. Once an auction had begun, generally one bidding round per day occurred. An auction closed if one round passed in which no bidder submitted a new acceptable bid on any license. Bidding stopped on all licenses simultaneously. 9 Table 3. PCS auction structure BLOCK

BLOCK

GEOG.

AUCTION

AUCTION

NAME

SIZE

BREAKD

START

END

 

 

 

 

 

A

30 MHz

MTA

12/5/1994

3/13/1995

B

30 MHz

C

30 MHz

MTA

12/5/1994

3/13/1995

MTA

12/18/1995

5/6/1996

D

10 MHz

BTA

8/26/1996

1/14/1997

E

10 MHz

BTA

8/26/1996

1/14/1997

F

10 MHz

BTA

8/26/1996

1/14/1997

67

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

A, B, and D block auctions were one hundred percent successful. No licenses were in default and reclaimed by the FCC. E and F bandwidth auctions were also highly successful, with few defaults.10 However, in the C block, with the twin characteristics of 30 Mhz of bandwidth and entrepreneurial status, the default rate was high; eighty percent of this bandwidth was reauctioned. Speculative bidding was an issue particularly for C block auctions. While both the C and F blocks were entrepreneur blocks, C block spectrum generally commanded a higher price because of its greater bandwidth. Numerous winning bidders defaulted when they lacked the financial backing to build out systems and were unable to resell their licenses profitably. Some winning bids may have been cast on a speculative basis by bidders with no serious intent of building out PCS systems. Several smaller regional bidders did successfully acquire spectrum, mostly 10 Mhz spectrum in non-entrepreneurial blocks or in the 10Mhz entrepreneurial F block, and built out regional wireless service. Two cases of C block defaults, GWI PCS and NextWave, were litigated up to the U.S. Supreme Court. GWI PCS was the high bidder for fourteen C-block licenses, totaling approximately $1.06 billion. A U.S. bankruptcy court subsequently voided $894 million of GWI’s obligations to the FCC, sustaining the argument that, at the time GW I actually took possession of the licenses, the licenses had significantly depreciated in value. The Supreme Court declined to reconsider this case. GWI and its affiliates today are providers of landline phone and internet service. NextWave was the successful bidder on 86 licenses, mostly C block licenses, for a total of $4.7 billion. When NextWave defaulted, the FCC repossessed the licenses and reauctioned them. Verizon, the top bidder in this auction, agreed to pay $8.8 billion for 133 (now subdivided) licenses. Cingular (now AT&T) and other carriers also successfully bid on this spectrum. In October 2002, the U.S. Supreme Court held that

68

bankruptcy law precluded the FCC from revoking the licenses.11 In 2004, the FCC and NextWave reached a settlement distributing the spectrum among Cingular, (17 %), NextWave (10%) and the FCC (72%). NextWave’s subsequent behavior supports the assertion that its activity in the PCS auctions was primarily speculative.12 In 1999, the FCC partitioned some of the C bandwidth into 15 Mhz blocks; for the 2001 auctions of remaining C block spectrum, the bandwidth was further partitioned into 10 Mhz. FCC subdivision of the initial 30 Mhz C block spectrum into narrower bandwidths reflects the nonviability of reserving wide bandwidth (30Mhz) solely for entrepreneurial bidders.

Constrained market forces determine industry structure While the FCC auction structure set an upper limit on the number of PCS competitors, the initial number of potential competitors was determined by the auction outcome. Despite an upper bound of six competitors built into the auction design, the auction outcome, market-driven, was decidedly more concentrated. The two winners of the greatest number of auctions, Sprint/Wireless LP and ATT, achieved penetration rates of 93 and 94 percent respectively. The penetration rate measures the percentage of total MTA’s in which a company acquired spectrum. The mean penetration rate of the twenty most successful bidders was 27.4 percent. In major blocks A and B, the two greatest winners, Sprint and ATT, claimed over fifty percent of total spectrum auctioned; the four greatest winners acquired over seventy percent. In D block auctions, the two largest winners, once again Sprint and ATT, claimed thirty and twenty-five percent of spectrum, respectively. In the E block auctions, the two largest winners, again Sprint and ATT, acquired fifteen and twenty percent, respectively.

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Table 4. Initial PCS auction outcomes B idder W irelesLP ATT P rim eco W stnP C S N xtw ave A m erP ort S print GTE P ow ertel OPCSEGl S W B ell B ellS outh A llT el A m eritech P acT eles O m nipt U S W est M ercury

S pectrum % total spectrum (M H z) 9510 8220 3330 2310 1990 1890 1570 1290 1090 1050 1030 1010 740 630 600 600 420 240

Bidding across bandwidths was the strategy used by the two major auction winners to assemble a map of broad PCS coverage. Sprint and its partners acquired A or B licenses in 29 MTA’s and then acquired 128 D licenses and 31 E licenses in 15 additional MTA’s, yielding the Sprint partnership 188 licenses in 45 MTA’s. ATT won A/B licenses in 21 MTA’s and then acquired 128 D and 107 E block licenses, a total of 256 licenses spanning 45 MTA’s. Omnipoint and OPCSE Galloway (a.k.a. Omnipoint) jointly obtained spectrum in approximately half of the MTA’s. Two other major bidders each acquired spectrum in about one-half of the MTA’s. The two greatest winners, ATT and Wireless LP/Sprint, acquired over 40 percent of the spectrum successfully auctioned. Table 4 displays the PCS auction results for bidders who obtained more than one percent of total spectrum auctioned, or who were successful in at least five auctions. The auction results were significantly more concentrated than the auction design. The auction design increased the transaction costs of spectrum ownership and the outcome suggests that a more

#M T A 's 0.163 0.141 0.057 0.04 0.034 0.032 0.027 0.022 0.019 0.018 0.018 0.017 0.013 0.011 0.01 0.01 0.007 0.004

% total M T A 's 29 45 11 21 27 6 16 4 6 23 10 8 12 2 2 1 9 5

0.6 0.94 0.23 0.44 0.56 0.13 0.33 0.08 0.13 0.48 0.21 0.17 0.25 0.04 0.04 0.02 0.19 0.1

concentrated auction design would have distributed PCS spectrum more efficiently.

Early PCS buildout The FCC required PCS licensees to make their services available to one-third of the population in their service areas within five years and to two-thirds within ten years. Major auction winners increased their market shares by purchasing leases in secondary markets and by mergers/acquisitions. In 1998, for instance, three of 1997’s top 25 operators in subscribership had consolidated with other carriers.13 A primary motivation was the desire of larger regional carriers to capture economies of scale and minimize roaming charges, so that they could compete effectively with national operators like ATT and Sprint. By 1998, fourteen companies had built out PCS service in a total of thirty-seven MTA’s 14. Sprint offered PCS service in 36 MTA’s, a penetration rate of 87.8 percent. PrimeCo (now Verizon) pro-

69

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

vided PCS service in 10 MTA’s, and ATT offered PCS service in 15 MTA’s. Most built out licenses were in the A and B blocks. Population and population growth were significant factors determining early PCS buildout.15 Among BTA’s in the top quartile (the most populated BTA’s), 98 percent had one or more new entrant providing PCS service, while in the bottom quartile, only 41 percent of the BTA’s had PCS coverage.16 Possible reasons: higher expected profitability from a larger pool of potential customers, and the desire to offset the higher spectrum price in more populated areas17 with an earlier stream of returns.

Role of municipal governments in the development of the wireless industry Wireless development created a conflict between municipalities’ longstanding power to oversee land use and the federal mandate to build out wireless systems. The federal Standard Zoning Enabling Act of 1926 had led to the development of comprehensive zoning ordinances in many municipalities. Zoning ordinances typically define and limit the types of activities and structures allowable in designated districts. These regulations are meant to mitigate the negative externalities that a real estate owner’s use of his/her property might impose on other members of the community, and thus to protect property values. The build-out of PCS infrastructure required the erection of monopoles and towers on which to site wireless antennae, especially in areas lacking tall buildings. The need for towers increased dramatically, both because of the increasing demand for wireless service and because the use of PCS spectrum (located at a higher frequency range) required towers closer together than the older cellular technology.

70

Communities, especially in urban and suburban areas, opposed tower construction, citing aesthetic and property value concerns. Because the wireless industry relies on radio frequency bands for signal transmission, some municipalities even raised issues of health. The Telecommunications Act of 1996 (TCA) prevented municipalities from denying permission for cell tower construction solely based on health arguments, giving the FCC express regulatory power over wireless facilities’ radio frequency emissions. Some municipalities passed ordinances banning cell towers from certain locations, and municipalities began to amend their zoning ordinances to require permitting approval prior to cell tower construction18. As of September 25, 1997, tower siting moratoria had been enacted in 202 municipalities in 23 states. These moratoria, enacted primarily in urban areas, affected a population of over six million people.19 The cell tower controversy has not abated. In 2007, the town of Acton, Ma. voted to temporarily ban new cell tower construction, while the town studied tower placement issues.20 The FCC attempted to mediate the conflicting interests of local governments/citizens and the wireless industry. In August 1998, the FCC announced a facilities siting agreement between the Commission’s Local and State Government Advisory Committee, the Cellular Telecommunications Industry Association, the Personal Communications Industry Association and the American Mobile Telecommunications Association. To quote FCC Chairman Kennard, “(t)he towers and antennae …are essential …to these new (wireless) technologies. On the other hand, local governments and citizens clearly have a legitimate interest in where and how towers are sited.” The joint agreement involved appropriate guidelines for tower and antennae siting, establishing a set of best practices, as well as an informal dispute resolution process for siting issues.21 When municipalities have failed to grant permission for tower construction, citing moratoria or zoning ordinances, wireless companies have

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

frequently filed lawsuits to permit construction. Courts have often shown a willingness to favor the federal Telecommunications Act over the wishes of local regulators. In Sprint Spectrum L.P. v. the City of Medina (1996), a federal district court upheld Medina, WA’s six-month tower moratorium as an appropriate use of the city’s authority to determine telecommunications policy and procedures. However, in Illinois RSA No.3 v. County of Peoria (1997), a federal district court overturned a county’s decision denying a plaintiff’s request for a cellular tower, ruling that adequate reasons for the denial had not been given and that the mere existence of opposition is insufficient to support denial.22 A landmark case regarding cell tower erection is Omnipoint Communications MB Operations LLC v. Town of Lincoln, decided in August 2000.23 This decision limited a municipality’s authority to use a zoning ordinance to limit cell tower construction The U.S. District Court held that the town’s “application of (its) zoning ordinance had created (a) substantial gap in coverage within (the) town, and thus had (the) effect of prohibiting provision of wireless services in violation of (the)TCA.” The Court found that “ A universal technological advance cannot be permanently stayed by a local stratagem devised to preserve the character and beauty of a locality. The enduring principle of local control of land use shall be honored, but only if a federal law which promotes the establishment of a comprehensive nationwide wireless communication network is not thereby subverted.” 24 Citing earlier cases, the Court stated that the 1996 Telecommunications Act was passed “in order to provide a procompetitive…framework…to accelerate rapidly private sector deployment of advanced telecommunications and information technologies…. The TCA significantly limits the ability of state and local authority to apply zoning regulations to wireless telecommunications. Under the TCA, the power of local governmental authorities to regulate the placement, construction, and modification of

WCF’s (wireless communications facilities) is tempered by the proviso that such regulation shall neither discriminate among providers of personal wireless service nor prohibit … the provision of personal wireless service.” 25

Wireless industry: 2002 By 2002, digital technology was prevalent on the cellular spectrum. The distinction between PCS and cellular service was no longer discernible to the typical consumer. There had been considerable PCS buildout. Three wireless companies offered PCS service in most or all MTA’s. Two of these, Sprint and ATT, had acquired spectrum at auction. The third, VoiceStream, emerged as an industry player through mergers and acquisitions. Significant vertical integration occurred between 1998 and 2002. Companies merged and otherwise acquired spectrum to build out more nationwide service. Three of the five nationwide wireless companies that were dominant market players in 2002 (VoiceStream, Cingular and Verizon) were the result of mergers and acquisitions since 1998.26 The permissive attitude of the FCC allowed mergers and acquisitions which dramatically altered the industry’s structure from the auction design of the previous decade. Western PCS (owned by Western Wireless) had successfully bid on PCS spectrum and by 1998, its division, Voicestream, had built out service in several license areas. In 1999, VoiceStream was spun off from Western Wireless. VoiceStream merged with Omnipoint and Aerial (a/k/a American Portable) in 2000 and with Powertel in 2001. In May 2001, Deutsche Telekom AG completed its acquisition of VoiceStream. By 2002, VoiceSteam offered PCS service in 44 MTA’s. In September 2002, the VoiceStream brand name was changed to T- Mobile. Cingular’s27 history originated with the postDivestiture Baby Bells. Cingular was formed in

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The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

2000 as a joint venture of SBC and Bell South, two Baby Bells that had successfully bid on PCS spectrum (Table 4). During the PCS auctions, SBC was called Southwestern Bell. Southwestern Bell changed its name to SBC Communications in 1995. In 1998, SBC acquired Pacific Telesis ( a holding company for Baby Bells Pacific Bell and Nevada Bell), which had also acquired PCS spectrum at auction. In 1999, SBC merged with Ameritech, a regional holding company for six Baby Bells. Ameritech was also a PCS auction winner. Despite the increased concentration resulting from this merger, the FCC determined that, with conditions, the SBC/Ameritech merger was in the public interest and would strengthen rather than reduce competition.28 Consequently, SBC controlled three of the seven regional Baby Bells established under the terms of the Divestiture Agreement with AT&T. The formation of Cingular in 2000 further increased SBC’s market position. Prior to these mergers and acquisitions, the participating Baby Bells had begun to build out PCS licenses in their service areas, and this build out continued under SBC. By 2002, Cingular offered PCS service in thirteen MTA’s. However, Cingular’s total wireless coverage was much greater. Cingular’s Baby Bells, as local landline companies, had acquired cellular licenses and built out cellular networks in the 1980’s. According to the FCC, by 2001, Cingular was the second largest provider of wireless services. 29 Mergers and acquisitions also created Verizon Wireless. Two regional Baby Bells, Bell Atlantic and NYNEX, had merged in 1996 as Bell Atlantic. In 1998, Bell Atlantic and GTE entered into a merger agreement. Bell Atlantic was a provider of cellular service, while GTE had acquired PCS spectrum at auction (Table 4) and had begun to build out service. While the Department of Justice (DOJ) was reviewing the Bell Atlantic/ GTE merger, GTE expanded its wireless licenses by acquiring half of Ameritech’s assets.30

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DOJ opposition to the Bell Atlantic/GTE merger centered around Bell Atlantic’s interest in PrimeCo.31 The DOJ alleged that the merger would reduce competition in nine states. The consent decree required that overlapping wireless service be sold off to other providers.32 In June 2000, Bell Atlantic acquired GTE, and renamed the merged entity Verizon Communications. Meanwhile, in 1999, Bell Atlantic and Vodafone Airtouch announced their intention to form Verizon Wireless. Airtouch (Pac Tel Cellular) had just completed a merger with British Vodafone. The DOJ filed a civil antitrust complaint, claiming that the combined effects of the Bell Atlantic/GTE merger and the Bell Atlantic/Vodafone partnership would reduce wireless competition. A revised consent decree required further divestiture of assets in regions where both Bell Atlantic and Vodafone offered wireless service.33 While the DOJ’s consent decrees had the apparent effect of preserving the level of competition in the wireless industry, these mergers in fact created a large wireless provider with considerable market power. Bell Atlantic’s interest in PrimeCo, noted previously, eventually led to the inclusion of PrimeCo in the Verizon group. PrimeCo, formed in 1994 as a joint venture of Bell Atlantic, NYNEX, U.S. West and Airtouch, bid in the PCS auctions, acquiring licenses in eleven MTA’s (Table 4). The Bell Atlantic/NYNEX merger, and AirTouch’s purchase of the U.S. West shares, resulted in joint ownership of PrimeCo by Bell Atlantic and AirTouch. When AirTouch was purchased by Vodafone, Bell Atlantic exercised its option to dissolve PrimeCo34 and divide its licenses between itself and Vodafone. As noted earlier, Vodafone and Bell Atlantic then partnered to form Verizon Wireless. The FCC justified the numerous mergers and acquisitions which it approved during this period, most notably VoiceStream, Cingular and Verizon, on the basis of the economies of scale35. These mergers and acquisitions across MTA’s resulted

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Table 5. PCS and total wireless service provider C om pany

#M T A :P C S P C S P E N E T R A T IO N # M T A :total w ireless T O T A L P E N RATE (P C S +cellular) RATE S print 48 1.000 48 1.000 ATT 46 0.958 48 1.000 V oicestr 44 0.917 44 0.917 C ingular 13 0.271 38 0.791 A lltel 1 0.021 3 0.063 C ric/L 12 0.250 12 0.250 V eriz 14 0.292 44 0.917 Q w est 3 0.063 3 0.063 N extel 0 48 1.000 U S C ellular 0 4 0.083 other*(total) 8 0.021 9 0.021 m ean

in increased vertical concentration of the wireless industry. To quote the FCC in its Fifth Annual CMRS Report, “operators with larger footprints can achieve economies of scale and increased efficiencies compared to operators with smaller footprints. Such benefits permit companies to introduce and expand innovative pricing plans, reducing prices to consumers,” intensifying competition among nationwide providers 36. In November 2001 the FCC raised the spectrum cap for individual wireless companies from 45 to 55 MHz per urban market, and voted to eliminate the cap entirely in January 2003. Raising and eventually eliminating the ceiling on the amount of spectrum for which a provider could acquire leases enabled greater concentration in the wireless industry.37 By 2002, the major wireless operators, in descending order, were Verizon, Cingular, AT&T, and Sprint.38 VoiceStream also had a major nationwide presence, though its number of subscribers trailed the top four. Sprint, AT&T and VoiceStream had built out PCS service in all or most of the MTA’s in continental United States. Verizon and Cingular, in contrast, were still providing service to the vast majority of MTA’s they serviced using cellular bandwidth, gradually converting this

0.246

0.330

service from analog to digital systems. Nextel also had a nationwide presence in the wireless industry through its ESMR service. Table 5 shows provider penetration rates, by MTA, for both PCS service and total wireless service.

The Wireless Industry: 2004 By 2004, the marketplace distinction between cellular and PCS service was nonexistent. Service was increasingly digital rather than analog, regardless of the spectrum used for transmission. We continue to discuss PCS buildout because PCS service was the growth segment of the wireless industry. From 2002 to 2004, buildout of PCS licenses continued39. The average number of PCS competitors in each of the 48 primary MTA’s increased from 4 in 2002 to 4.6 in 2004. Most of this expansion, however, occurred as cellular providers acquired PCS bandwidth in order to increase their call capacity and provide customers with better coverage and fewer dropped calls. Average total providers per MTA was virtually unchanged: 6.38 in 2002 v. 6.65 in 2004.

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The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

While in 2002, eight wireless providers serviced only a single MTA, by 2004, there was no single-MTA provider. Single-MTA providers had either broadened their field of service, discontinued service, or merged/were acquired. Every PCS provider with a 2002 penetration rate of less than one hundred percent increased its penetration rates from 2002 to 2004. The mean PCS penetration rate rose from 24.6 percent in 2002 to 41.5 percent in 2004. Two of the three dominant PCS providers had 100 percent market penetration rates in 2004, compared with one provider in 2002. Penetration rates also increased in the total wireless industry, driven by increased penetration in the PCS segment. The 2004 mean penetration rate was 60.25 percent, compared to a 2002 penetration rate of 33.02 percent. Four wireless providers had penetration rates of 100 percent by 2004. Several regional companies also provided wireless service. The acquisitions and mergers that took effect prior to the fall of 2004 were vertical, or interregional, in nature. These acquisitions and mergers had the effect of yielding more companies with nationwide coverage, but did not reduce intraregional competition. As noted previously, the mean number of PCS providers per MTA rose from 1998 to 2004, and the mean number of wireless providers rose through 2002 and then remained relatively constant.

Horizontal mergers reduce competition •

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Cingular/AT&T The nature of wireless mergers changed dramatically in 2004. In February 2004, Cingular, the second largest provider, had entered into an agreement to acquire AT&T Wireless, the third largest wireless provider, spun off from AT&T Corp in 2001.40 In October 2004, the Justice Department’s anti-trust division and the FCC approved Cingular’s takeover of

AT&T Wireless, to form the largest wireless company in the United States. 41 The settlement required Cingular to divest assets in thirteen markets. According to the Justice Department complaint, Cingular Wireless and AT&T Wireless were two of six nationwide mobile wireless providers; the proposed transaction would reduce competition for wireless telecommunications services in ten markets, and reduce competition for wireless broadband in three additional markets.42 In nine of these ten wireless telecommunications markets, Cingular and AT&T Wireless were, or held interests in, the two largest incumbent wireless providers, and in all ten markets, the merged firm would be the largest.43 The FCC had found that the merger of Cingular and AT&T Wireless resulted in a “sharp drop in the percentage of the population living in counties with more than six providers, (w)hile the percentage of the U.S. population living in counties with three or more, four or more, or five or more mobile telephone carriers (was) unchanged.”44 Evidence of the decrease in competition resulting from the Cingular/ AT&T Wireless merger is found in a comparison of the HHI’s45 reported in the FCC’s Annual CMRS Competition Reports for 2004 and 2005. The FCC computes HHI’s for Economic Areas to provide information on the competitiveness of wireless markets in these Areas. Because wireless spectrum was allocated by MSA’s and RSA’s (for cellular spectrum) and by MTA’s and BTA’s (for PCS spectrum), the geographic entities for which the DOJ required Cingular/AT&T spectrum divestiture do not align with the geographic entities for which HHI values are available. However, for geographic entities where comparison was possible, we compared pre and post-merger HHI values, as reported by the FCC. In three of the four comparisons, by the FCC’s own metric, there was a significant decrease in competition after the merger: Shreveport, LA:

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

2524 v. 3387; Oklahoma City, OK: 1836 v. 3714; Dallas/Fort Worth Tx: 1743 v. 2708; Topeka KN: 1783 v. 1760. The FCC did not provide a compelling argument that its approval of this merger was consistent with its Congressional mandate, in the Omnibus Budget Reconciliation Act of 1993, to promote competition in the wireless industry. In the 2005 CMRS Report, the FCC stated: “in industries where the scale of output at which a firm can fully exploit scale economies is large relative to potential demand, there will be room in the market for only a small number of firms operating at the lowest possible costs.”46 The question of whether there are economies of scale of sufficient magnitude to justify this merger was never addressed. The FCC had cited, in its 2004 CMRS Report, the Cingular claim that the combined entity would generate more that $1 billion in operating and capital expenditure savings in 2006 and in excess of $2 billion in annual savings beginning in 2007.47 The validity of these alleged savings, or their effect on Cingular’s pricing, were not reported. The argument for horizontal mergers on the basis of economies of scale is premised upon the realization of cost savings that are passed forward to consumers as lower prices. In his Concurring Statement in the 2005 CMRS Report, Commissioner Copps commented that while Congress tasked the FCC with doing “an analysis of whether or not there is effective competition in commercial mobile services, the failure to define “effective competition” “limits the ability of the Commission and the Congress to rely on our results.”48 •

Sprint/Nextel The movement toward horizontal concentration continued. In December 2004, Sprint announced plans to acquire Nextel. On August 12, 2005, having received regulatory approval from the FCC and the DOJ, the companies completed the merger.49Sprint Nextel asserted at the time

that they were positioning the company for “a seamless integration” of wireless service. These two mergers/acquisitions had the effect of reducing the average number of wireless providers per MTA by approximately thirty-three percent. The achievement of economies of scale was relatively straightforward for Cingular, since both AT&T and Bell South had selected TDMA technology50 for their second-generation wireless networks.51 Sprint, in contrast, had selected CDMA technology52 for its wireless network,53 while Nextel used iDEN54, with included a digital two-way radio feature like a walkie-talkie. Achieving economies has proved more difficult for Sprint/Nextel. While the merger provided the company with scale, Sprint continues to struggle to knit together two very different phone networks (CDMA v. iDEN) and customer groups.55 •

AT&T/Bell South Another horizontal merger that reduced competition was the merger of AT&T with Bell South in 2006. In early 2005, SBC announced its intent to purchase AT&T Corp., a merger that was approved by the DOJ and the FCC and finalized in November 2005. SBC then changed its corporate name to AT&T. In March 2006, AT&T announced its proposed merger with Bell South. Although AT&T and Bell South did not compete directly in the local, long-distance or broadband markets, they competed for business customers. Further, the merger would give AT&T complete ownership of Cingular (a joint venture of SBC and Bell South). On October 11, 2006, the DOJ’s antitrust division issued a statement approving the merger unconditionally: “After thoroughly investigating AT&T’s proposed acquisition of Bell South, the antitrust division determined that the proposed transaction is not likely to reduce competition substantially. The merger would likely

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The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

result in cost savings and other efficiencies that should benefit consumers.”56 There was significant opposition to the DOJ ruling. Smaller phone-company rivals, Democrats on the FCC, and consumer groups complained57 that the DOJ had abdicated its responsibility to scrutinize whether the new company would be so big that it could reduce competition.58 FCC Commissioner Copps argued that the DOJ had walked out on consumers and small businesses by refusing to impose even a single condition in the largest telecom merger the nation had ever seen.59 Commissioner Adelstein called the decision “a reckless abandonment of DOJ’s responsibility to protect competition and consumers.”60 Most of these concerns focused on wireline phone and broadband services (TV and internet), rather than the wireless segment. After having delayed its vote,61 on December 29, 2006, the FCC approved the merger, concluding that significant public interest benefits were likely to result. For the wireless industry specifically, the FCC concluded that benefits would include “improved wireless products, services and reliability due to the efficiencies gained by unified management of Cingular….”62 As with the previous Cingular merger, the FCC did not explore the magnitude of economies of scale in the wireless industry nor did the FCC define what it considered to be effective competition.

To “facilitate the speediest possible approval of the merger”, AT&T had agreed to several voluntary, enforceable commitments.63 These commitments dealt primarily with broadband, and included a commitment to network neutrality. The primary wireless commitment was the reassignment /transfer to an unaffiliated third party all 2.5 GHz spectrum (broadband radio/educational services) and the commitment to offer service in the 2.3 GHz band to 25% of the population in the service area of AT&T/BellSouth wireless communications licenses.64

AWS spectrum: 2006 In 2006, the FCC auctioned 1,122 licenses for 90 megahertz of AWS (Advanced Wireless Services) spectrum at 1710-1750 and 2110-2155 MHz. This spectrum, previously used by federal operators, can be used for a variety of wireless services, including Third Generation (3G) mobile broadband and advanced wireless services. AWS auctions followed the PCS auction structure of dividing spectrum into six frequency blocks (A-F). PCS licenses were allocated to 50 MTA’s and 493 BTA’s. AWS licenses were auctioned by twelve multi-state Regional Economic Areas (REAG), 176 Basic Economic Areas (BEA), and 734 highly- disaggregated Cellular Market Areas (CMA). Table 6 shows the structure of the AWS auctions.

Table 6. AWS auction structure

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B LO C K NAME

B LO C K G EOG S IZ E BREAKD

A B C D E F

20M H z 20M H z 10M H z 10M H z 10M H z 20M H z

CMA EA EA REAG REAG REAG

# A U C T IO N A U C T IO N LIC E N S E S S T A R T END 734 176 176 12 12 12

08/09/06 08/09/06 08/09/06 08/09/06 08/09/06 08/09/06

09/18/06 09/18/06 09/18/06 09/18/06 09/18/06 09/18/06

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Table 7 displays the ten highest winning bidders, by provisionally winning bets (PWB). 65 T op T en B idders b y P rovisionally W inning B ids ( P W B ) T otal # licenses Bidder PWB's R E A G B E A C M A PWB Total T -M obile C ellco d /b/a V erizon S pectrum C o LLC M etro P C S C ingular C rick et D enali S pectrum B arat W ireless A W S W ireless A tlantic W ireless

120 13 137 8 48 99 1 17 154 15

The AWS auctions offered discounts or bidding credits to smaller businesses that qualified as designated entities. A small business, defined as a bidder with average gross revenues between $15 million and $40 million for the preceding three years, received a 15 percent discount on its winning bid. A very small business, defined as a bidder with average gross revenues not exceeding $15 million for the preceding three years, received a 25 percent discount on its winning bid. Unlike the PCS auctions, however, there were no entrepreneurial blocks limited exclusively to smaller businesses. Moreover, the experience of the PCS auctions showed that larger companies had won entrepreneurial discounts by partnering with smaller firms eligible for discounts. To close this loophole, the FCC approved new rules in April 2006 which extended from five to ten years the period before which a winning smaller business could sell its licenses to another carrier, and placed further restrictions on leasing spectrum or partnering with other carriers. One hundred two designated entities qualified to bid, comprising 61 percent of total bidders. 58 of these qualified as very small businesses and 44 qualified as small businesses. The AWS auctions were largely successful. Of 1122 licenses auctioned, 1087 licenses were

10 4 1 2 3 1 1 1 1 0

17 2 136 6 24 25 0 5 48 14

93 7 0 0 21 73 0 11 105 1

$4,182,312,000 $2,808,599,000 $2,377,609,000 $1,391,410,000 $1,334,610,000 $710,214,000 $365,445,000 $169,520,000 $115,503,000 $100,392,000

successfully placed. In the REAG auctions, all licenses available in continental United States, Hawaii and Puerto Rico were successfully placed. In the BEA auctions, three licenses were held by the FCC. The vast majority of auction failures occurred in the highly disaggregated CMA auctions. Of the six top winning bidders, three (T Mobile, Verizon, and Cingular) were wireless companies already offering nationwide service. Spectrum Co. LLC was formed as a consortium of cable owners Comcast, Time Warner, Cox, and Brighthouse, and Sprint. Metro PCS, and Cricket (a/k/a Leap), were established regional providers. The highest bidder, T Mobile, the fourth largest wireless company, was quoted as saying that its new licenses doubled its average capacity in the top 100 U.S. markets and that it expects to spend nearly $2.7 billion on a network upgrade that can deliver mobile multimedia capabilities that its rivals currently offer.66 Cellco d/b/a Verizon, the nation’s number two wireless provider, acquired sufficient spectrum, according to one analyst, to build a new nationwide wireless network, perhaps devoted exclusively to mobile TV or high speed wireless internet access.67 The four last bidders in the top ten list, shown by bidding name, are non-providers and thus seem

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The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

to have the potential to expand competition. In fact, however, three of these bidders, all of whom qualified for bidding credits as Designated Entities, were affiliated with and/or funded by existing wireless providers. Denali Spectrum received a 25 percent bidding credit. Denali was funded by Cricket/Leap68, an existing regional provider that was not eligible for bidding credits. Similarly, Barat was awarded a 25 percent bidding credit. US Cellular, which provides wireless services in Chicago, Milwaukee, San Antonio,and Portland, Oregon, is a limited partner in Barat and provided initial funding for Barat’s participation in the AWS auctions.69 While US Cellular did not acquire any AWS licenses in its own name, the Barat licenses both expanded US Cellular’s market area and deepened its infrastructure in its core areas. AWS Wireless, the top bidder in terms of licenses won, is a wholly owned subsidiary of NextWave Wireless Inc. AWS Wireless did not receive any bidding credits. NextWave Wireless does not currently offer wireless services, nor does its parent corporation, NextWave Telecom Inc. 70 Atlantic Wireless, which received a 25 percent bidders’ credit, is an authorized Verizon dealer in Maryland, New Jersey and Virginia. Moreover, Atlantic is backed by some of the same investors supporting Aloha Partners, a start-up that has major cellular spectrum holdings.71 The AWS auction structure, with three overlapping geographic groupings, enabled major providers to acquire additional spectrum without directly competing. The AWS auction results (Table 7) show that this occurred, either coincidentally or collusively. In the REAG auctions, the three largest winners were T Mobile, Verizon, and Cingular. Spectrum Co., on the other hand, focused on the BEA auctions, where it acquired 136 PWB’s. There are two ways in which the spectrum licensed at the AWS auctions potentially could have increased competition in the wireless in-

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dustry.72 First, a potential competitor in a region was created when a non-provider in a geographic area won spectrum. Second, an existing provider acquired spectrum, enabling deepening of coverage and upgrades that enhanced the provider’s long-term survival. Although numerous companies were successful bidders, the major AWS winners, discussed previously, were mostly existing wireless providers, or small businesses funded by existing providers. Thus the primary effect of the AWS auctions was a deepening of spectrum for existing providers. However, two regional providers, Metro PCS and Cricket, won spectrum that will enable them to enter major markets such as New York City, Philadelphia, and Washington, D.C. To examine the effect of AWS spectrum on the number of competitors in each MTA, we mapped the AWS auction results for REAGs and BEAs onto the forty-eight major MTA’s73, the primary geographic designation in the PCS auctions. MTA’s are numbered in descending order by population, so wireless data displayed by MTA rank orders the results by population. On average, seventy-eight percent of all AWS spectrum successfully auctioned was acquired by existing providers to deepen their service capacity. On average, seventy- four percent of AWS spectrum was acquired by the three nationwide providers and Spectrum. In every MTA, a majority of AWS spectrum deepened the spectrum held by existing providers, rather than introduced new providers into the market. Further, deepening occurred primarily among major national providers, even when regional competitors were in that marketplace. Deepening of spectrum holdings by existing providers is not necessarily an undesirable outcome, as discussed earlier. More troubling is the finding that much of the spectrum not acquired by existing providers was won by entities not currently providing service and whose spectrum winnings seem insufficient for them to enter the market as competitors.

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Table 8 displays information on CMA and BEA licenses acquired by minor bidders who do not currently provide wireless service. The nonproviders in Table 8 each acquired fewer than ten CMA or BEA licenses, and no REAG licenses. Reviewing the first data row, eleven bidders not qualifying for bidding credits each acquired one CMA license. Eight bidders qualifying for a 15% credit each acquired one license, and thirteen bidders qualifying for a 25% credit each acquired one license. Summarizing the first section of Table 8, a total of 69 bidders acquired fewer than ten CMA licenses, and did not win any BEA or REAG licenses. Summarizing the second section of Table 8, a total of eleven bidders had a combined total of fewer than ten CMA and BEA licenses, and no REAG licenses. This means that 80 out of the 104 total bidders in AWS auctions acquired such small slivers of spectrum that their industry participation does not seem viable.

It would seem that this spectrum is mostly being held by speculators. As can be seen from Table 8, in many cases, the price paid for the spectrum was reduced by bidding credits. Such an outcome is inefficient. It deprives the public of access to this spectrum and may enable the speculators to reap future windfall profits.

700 MHz spectrum: 2008 Auction 73, which began January 24, 2008, auctioned off 62 MHz of spectrum in the 700 MHz band, spectrum now in use by television broadcasters.74 1099 licenses in total were auctioned off, in five different blocks, by geographic area. The geographic structure of these auctions parallels the structure of the AWS auctions, with licenses auctioned by Economic Areas, Cellular Market Areas, and Regional Economic Area Grouping.

Table 8. AWS results for bidders acquiring < 10 #C M A licenses w on

0 bid credits 15% c redit 25% c redit 1 2 3 4 5 6 7 8 9

11 9 3 1 0 1 2 0 1

8 7 3 2 1 1 1 0 0

13 4 0 0 1 0 0 0 0

0 0 1 0 1 1 1 1 0

0 0 0 1 0 1 0 0 1

1 1 0 1 0 0 0 0 0

#B E A /C M A licenses w on 1B E A /0C M A 2B E A /0C M A 4B E A /0C M A 1B E A /2C M A 1B E A /3C M A 2B E A /3C M A 2B E A /6C M A 3B E A /2C M A 3B E A /5C M A

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The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

The system of small business bidding credits for Auction 73 is the same as the system used in the AWS auctions. The 700 MHz spectrum is particularly desirable because signals broadcast in this spectrum travel relatively long distances and are not so susceptible to interference as higherfrequency waves. This spectrum block has the potential to increase the level of competition in the wireless industry. The auction plan included a $4.6 billion threshold or reserve price75, which when met, triggered open-access rules for one-third of the spectrum. The licensee for Band C, the widest block at 22 MHz, “will be required to provide a platform that is more open to devices and applications. This would allow consumers to use the handset of their choice in this spectrum block, subject to certain reasonable network management conditions that allow the licensee to protect the network from harm.”76 The FCC explained why it was imposing open-access rules: “the 700 MHz spectrum provides an important opportunity to apply requirements for open platforms for devices and applications for the benefit of consumers…. (H)owever, … it would not serve the public interest to mandate … requirements for open platforms … for all …700 MHz spectrum or to impose broader requirements, such as wholesale or interconnection requirements, for the C block.” Continuing the justification, “while it is easy for consumers to differentiate among providers by price, most consumers are unaware when carriers block or degrade applications, …thus making it difficult for providers to differentiate themselves on this score.”77

Concluding Remarks The wireless telephony market is a dynamic market. Constantly evolving technologies have driven the industry’s expansion. For these reasons, it has been challenging for the FCC to implement its Congressional mandate to promote competition

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in the industry. The FCC has structured spectrum auctions with the goal of promoting competition. However FCC approval of horizontal mergers has had the effect of reducing the number of wireless competitors. At the municipal level, The Telecommunications Act has prevented cities and towns from limiting the number of wireless providers. As regional providers who have acquired AWS or 700 MHz spectrum build out infrastructure, in the short run at least, there will be an increase in competition in areas where these regional providers have expanded their footprint. Metro PCS, for instance, is currently in the process of obtaining the necessary municipal approvals to build out AWS spectrum licenses in the Northeast. Several factors may affect government’s future role in the evolving structure of the wireless industry. Auction structures for the PCS, AWS and 700 MHz auctions have allowed and in some instances encouraged speculation on wireless spectrum, creating a private-sector secondary market for the resale of spectrum leases. Such speculation creates market inefficiencies, denying consumers use of this spectrum, probably reducing competition and driving up wireless prices, and providing windfall profits to secondary-market license owners. The market structure of the industry would be improved if the FCC followed the example of many European regulators and subdivided available spectrum into larger units, rather than fragmenting it so greatly. Another issue is FCC implementation of its mandate to provide a competitive wireless marketplace. In the recent past, the FCC has justified both vertical and horizontal mergers that have reduced competition on the basis of economies of scale. The FCC uses the HHI index to measure competition. It would be useful if the justification of economies of scale were supported by some analysis of the cost structure of the wireless industry. Do economies of scale justify a reduction in the number of providers to three firms, to two firms?

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

How do Congress and the FCC define “effective competition?” The parameters for determining if a proposed merger reduces competition might be expanded to include the Grinnell Test78, a test that is typically used by the U.S. courts when adjudicating antitrust cases. Another possibility worth considering, given the dynamic nature of the industry, is examining whether barriers to innovation exist in the wireless market.79 Finally, decisions made at the federal, state, and local levels regarding the use of WiFi and WiMax technologies 80will influence the future structure of the wireless industry. WiFi currently uses license-exempt spectrum. Whether WiMax will ultimately use licensed or unlicensed spectrum is still undetermined. A related issue is whether these new wireless technologies will be provided by existing providers, or whether the regulators will allow a further consolidation of the market, with broadband providers providing a bundle of services which includes wireless telephony.

REFERENCES American Bar Association (editors). (2005). Telecom Antitrust Handbook ( American Bar Association Section of Antitrust Law Monograph). Boston Globe. (2007). Acton to vote on cell tower moratorium. Cellular News. (2006). DOJ Approves AT&T-Bell South Merger. Coase, R. H. (1959). The Federal Communications Commission. Journal of Law and Economics, 2, 1-40. Department of Justice (1999). Justice Department Requires Bell Atlantic and GTE to Divest Wireless Businesses in order to Proceed with Merger. Department of Justice (2004). Justice Department Requires Divestitures in Cingular Wireless’s Acquisition of AT&T Wireless.

Dunbar, J. (2006). FCC Delays Vote on AT&TBellSouth Deal. Associated Press. Electrical Engineering Times. (2007). FCC spells out rules for 700 MHz bands. EE Times. FCC News (1998). Chairman William E. Kennard Announces Historic Agreement by Local and State Governments and Wireless Industries on Facilities Siting Issues. FCC News (1999). FCC Approves SBC-Ameritech Merger Subject to Competition-Enhancing Conditions FCC News (2001). FCC Announces Wireless Spectrum Cap to Sunset Effective January 1, 2003. FCC News (2006). FCC Approves Merger of AT&T Inc. and BellSouth Corporation. Federal Communications Commission. (1998). Third Annual CMRS Competition Report. Federal Communications Commission. (1999). Fourth Annual CMRS Competition Report. Federal Communications Commission. (2000). Fifth Annual CMRS Competition Report. Federal Communications Commission. (2002). Seventh Annual CMRS Competition Report. Federal Communications Commission. (2004). Ninth Annual Report and Analysis of Competitive Market Conditions with Respect to Commercial Mobile Services. Federal Communications Commission. (2005). Tenth Annual Report and Analysis of Competitive Market Conditions with Respect to Commercial Mobile Services. Federal Communications Commission . ( 2007) Second Report and Order, 700 Mhz Bands. Financial Times (2008). Sell phone. Harris, N. (2000). The Basic Question Which wireless standard is best? A lot hangs in the balance. The Wall Street Journal.

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Harvard Law Review (Eds) (2001). Antitrust and the Information Age:Section 2 Monopolization Analyses in the New Economy. Harvard Law Review, 114, 5.

United States District Court for the District of Columbia (2000). United States of American v. Bell Atlantic, GTE and Vodafone Airtouch, Motion for Entry of Final Judgment.

Hazlett, T. W. (1998). Assigning Property Rights to Radio Spectrum Users: Why Did FCC License Auctions Take 67 Years? Journal of Law and Economics, 41, 45-67.

Webb, W. (2001). The Future of Wireless Communications. Boston, MA: Artech House.

Industry Canada. (2007). Consultation on a Framework to Auction Spectrum in the 2 GHz Range including Advanced Wireless Services. McDonough, C. (1999). The Price of Zoning Revisited: Zoning Issues Raised by the Telecommunications Act of 1996. Illinois Real Estate Letter, 13(1), 1-3.

Westlaw. High Plains Wireless, L.P., Appellant v. Federal Communications Commission, Digital PCS, LLC and Tritel Communications, Inc., Intervenors. Westlaw. Omnipoint Communications MB Operations, LLC v. Town of Lincoln D Mass, 2000, 107 F.Supp.2d.

McDonough, C. (2005) History of the Wireless Industry in the United States, report.

key terms

McDonough, C. (2007). The Impact of AWS on the Structure of the Wireless Telephony Industry. Paper presented at the 2007 Eastern Economics Association Conference, New York, New York.

Antitrust Laws: Laws enacted by the federal government to limit and control concentrations of economic power. The first antitrust law in the United States, the Sherman Antitrust Act, was enacted by Congress in 1890. Antitrust laws are enforced by the U.S. Department of Justice. Antitrust laws prohibit restrictions of free trade and competition, outlaw anti-competitive practices such as price fixing, and limit the scope of mergers and acquisitions.

McDonough, C. (2008). The Structure of the United States’ Wireless Telephone Industry:Theory, Reality and the Role of Government Regulation, International Telecommunications Society 17th Biennial Conference, Montreal. New York Times (1999). Holy War Over the Future of Wireless. Regli, B. J. W. (1997). Wireless: Strategically Liberalizing the Telecommunications Market. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc. Sprint Nextel News Release (2005). Sprint Nextel Completes Merger. Sterling, C., Bernt, P., & Weiss, M. (2006). Shaping American Communications. New York, N.Y.: Lawrence Erlbaum Associates.

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Competition: A market condition where price and output are determined by the collective market forces of supply and demand, rather than by an individual producer or group of producers. Among the factors that tend to lead to competition are ease of entry into an industry, number of competitors and market shares, and the substitutability among the products of the competing firms. Market Structure: The level of competition in an industry, that is, whether numerous firms compete with each other for market share or the industry is highly concentrated with few competitors.

The Impact of Government on the Evolving Market Structure of the U.S. Wireless Telephony Industry

Mergers and Acquisitions: The buying, selling and combining of different companies, often companies that produce similar or competing products or services. This is a tool used to enable a company to grow rapidly without having to construct an expanded business entity. Mergers and acquisitions typically reduce the amount of competition in an industry. The difference between a merger and an acquisition is that a merger is often undertaken consensually, while an acquisition may be the result of a takeover of one company by another. Wireless Spectrum: Bands within the electromagnetic spectrum that have been allocated for wireless communications, such as cellular bandwidth at 800-900 MHz and the PCS bandwidth in the 2 GHz range.

5





6

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8

Wireless Telephony: Telephone service which uses radiowaves, rather than a landline, to connect the person initiating a call to a telephone network. 9

Wireline Telephony: Telephone service which uses copper lines, or fiberoptic cables, to connect the person initiating a call to a telephone network.



10





11

Endnotes 1





2

3



4



Regli, B.J.W. (1997). Wireless: Strategically Liberalizing the Telecommunications Market. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc. 2 Annual CMRS Competition Report. Federal Communications Commission, July 3, 2002. Consultation on a Framework to Auction Spectrum in the 2 GHz Range including Advanced Wireless Services, Industry Canada, February 2007. Coase, R.H. (1959). “The Federal Communications Commission,” Journal of Law and Economics, 2, 1-40.

12



Hazlett, T.W. (1998). “Assigning Property Rights to Radio Spectrum Users: Why Did FCC License Auctions Take 67 Years?” Journal of Law and Economics, 41, 45-67. Some of this information on PCS auctions was presented in McDonough, C. (2008), The Structure of the United States’ Wireless Telephone Industry:Theory, Reality and the Role of Government Regulation, International Telecommunications Society 17th Biennial Conference, Montreal. The winner’s curse refers to the tendency for the winner to be the bidder who most overestimates the value of the item up for bid. “Reflexive bidding” is a tactic for deterring would-be competitors from bidding on a particular license by encoding bids. See High Plains Wireless, L.P., Appellant v. Federal Communications Commission, Digital PCS, LLC and Tritel Communications, Inc., Intervenors. FCC 94-178 Federal Communications Commission, Washington D.C. July 15, 1994. In the E block, there were six defaults (1%) and in the F block, there were two defaults (.4%) Supreme Court of the United States, Federal Communications Commission v. Nextwave Personal Communications, Inc et. al., October term, 2002. In April 2005, NextWave reorganized and sold NextWave Telecom, and its PCS spectrum, to Verizon for $3 billion. NextWave Wireless remains a corporate entity, and through its wholly owned subsidiary, AWS Wireless, successfully bid on spectrum in the AWS and other subsequent spectrum auctions. In April 2008, NextWave Wireless announced plans to put up for sale 223 licenses, including its AWS licenses, which together cover about eighty-four percent of the United States. (NextWave Plans to Sell Wireless Spectrum Positions, CNN

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Money.com, Dow Jones Newswires, April 23, 2008.) Fourth Annual CMRS Competition Report, Federal Communications Commission, June 24, 1999 Buildout information for the 41 largest MTA’s was obtained from these sources: wireless dimensions.com and data from providers’ websites. McDonough, C. (2005) History of the Wireless Industry in the United States, report. Fourth Annual CMRS Competition Report, op.cit. For example, the high bids for A/B spectrum were $443 million in MTA 1, $198 million in MTA 11, and $34 million in MTA 23. (MTA’s are ranked by population in descending order.) Typical of such regulation is the Andover Massachusetts Zoning Bylaw’s article (enacted October 2001) requiring the issue of a special permit for wireless communications devices. Included are design standards regarding setback, height, construction, and landscape, and an encouragement of co-location. Third Annual CMRS Competition Report, June 11, 1998, citing CTIA Siting Report Statistics, September 27, 1997. “Acton to vote on cell tower moratorium,” Boston Globe, May 6, 2007. “Chairman William E. Kennard Announces Historic Agreement by Local and State Governments and Wireless Industries on Facilities Siting Issues,” FCC News, August 5, 1998, McDonough,C. (1999) “The Price of Zoning Revisited: Zoning Issues Raised by the Telecommunications Act of 1996,” Illinois Real Estate Letter, 13(1), 1-3. Omnipoint Communications MB Operations, LLC v. Town of Lincoln D Mass, 2000, Westlaw, 107 F.Supp.2d 108. Ibid.

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Ibid. This history of the formation of VoiceStream, Cingular, and Verizon was presented in McDonough, C. (2008), op.cit. Cingular subsequently became the new AT&T. FCC News, “FCC Approves SBC-Ameritech Merger Subject to Competition-Enhancing Conditions,” October 6, 1999. Seventh Annual CMRS Competition Report, Federal Communications Commission, July 3, 2002. SEC, Form 8-K, “GTE to Acquire Ameritech Wireless Assets in Midwest,” April 5, 1999. Editors of ABA, “Telecom Antitrust Handbook( American Bar Association Section of Antitrust Law Monograph)”, 2005. Department of Justice, “Justice Department Requires Bell Atlantic and GTE to Divest Wireless Businesses in order to Proceed with Merger,” May 7, 1999. United States District Court for the District of Columbia, United States of American v. Bell Atlantic, GTE and Vodafone Airtouch, “Motion for Entry of Final Judgment” March 20, 2000. Telephonyonline, August 9, 1999 Fourth Annual CMRS Competition Report, Federal Communications Commission, June 24, 1999. Fifth Annual CMRS Competition Report, Federal Communications Commission, August 18, 2000. “FCC Announces Wireless Spectrum Cap to Sunset Effective January 1, 2003,” FCC News, November 8, 2001. Seventh Annual CMRS Competition Report, Federal Communications Commission, July 3, 2002. Data on PCS service providers, as of April 2004, were obtained primarily from wirelessadvisor.com

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Department of Justice, “Justice Department Requires Divestitures in Cingular Wireless’s Acquisition of AT&T Wireless,” October 25, 2004. Although DOJ anti-trust authorities required Cingular to offload assets in eleven states to ensure adequate competition in these markets, the overall effect of the acquisition was to reduce the level of intraregional competition Department of Justice and Network World (http://www.networkworld.com/edge/ news/2004/1025/cingudojr.html) Ibid. Tenth Annual Report and Analysis of Competitive Market Conditions with Respect to Commercial Mobile Services, Federal Communications Commission, September 26, 2005. The Herfindahl-Hirschman index (HHI) is calculated by summing the squares of the individual market shares of all firms competing in a market. When there is a single supplier, HHI takes a value of 10,000. The value of the HHI falls (to approach zero) as the structure of the market becomes more competitive. Tenth Annual Report, op.cit. Ninth Annual Report and Analysis of Competitive Market Conditions with Respect to Commercial Mobile Services, Federal Communications Commission, September 9, 2004. Tenth Annual Report, op.cit. Sprint Nextel Completes Merger, News Release, Sprint Nextel, Aug. 12, 2005. TDMA (time division multiple access) technology uses relatively narrow batches of wireless frequencies, which it then breaks up many times a second to convey many messages. Harris,N. (2000) “The Basic Question Which wireless standard is best? A lot hangs

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60

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in the balance,” The Wall Street Journal, September 18, 2000. CDMA (code division multiple access) technology breaks messages into small bits, which are then scattered throughout the wireless telephone spectrum and reassembled at their destination. “Holy War Over the Future of Wireless, New York Times, February 15, 1999. iDEN (Integrated Digital Enhanced Network) is a mobile telecommunications technology which provides its users the benefits of a two-way radio and a cellular telephone. “Sell phone,” Financial Times, January 21, 2008. M. Reardon, CNET News, October 11, 2006, quoting Thomas Barnett, assistant attorney general in charge of the Justice Department’s antitrust division. A.Schwartzman, CEO of Media Access Project, commented “ AT&T, with the help of a complicit government, is poised to control half the nation’s phone lines and also be the largest wireless … company. (Wait) until (consumers) get their next phone bill.” M.Reardon, CNET News, op.cit. “DOJ Approves AT&T-Bell South Merger”, Cellular News, 10/12/2006. Ibid. Dunbar, J. (2006) “FCC Delays Vote on AT&T-BellSouth Deal,” Associated Press, October 13, 2006. Ibid. FCC News, “FCC Approves Merger of AT&T Inc. and BellSouth Corporation,” December 29, 2006. Letter from Robert W. Quinn, Jr., Senior Vice President, Federal Regulatory, at&t, to M.L. Dortch, Secretary, Federal Communications Commission, December 28, 2006. Attachment, “Merger Commitments,” Letter from Robert W. Quinn, Jr., op.cit.

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FCC website, “FCC Advanced Wireless Services Auction No.66 ***Final*** Yahoo Finance, AP, Friday October 6, 2006 Business Week online, September 7, 2006 A Form 8-K was filed by Leap Wireless International, Inc., with the SEC on July 28, 2006, just prior to the start of the AWS auctions on August 9, 2006. Leap Wireless, operating under the Cricket brand, is a wireless provider in several markets including Pittsburgh, Denver, Phoenix, Memphis and Birmingham. Form 8-K reads: “On July 14,2006, Cricket …, a wholly-owner subsidiary of the registrant, Leap…, entered into a Credit Agreement … by … Cricket …as Lender, Denali Spectrum License, LLC …as Borrower, and Denali Spectrum, LLC …as Guarantor. The Borrower is a wholly owned subsidiary of the Guarantor. …Cricket has agreed to make loans to Borrower of up to $203.8 million to fund the payment of the net winning bids for licenses for which the Borrower is the winning bidder. Cricket has also agreed to loan the Borrower an amount equal to $1.50 times the aggregate number of potential customers covered by all licenses for which the Borrower is the winning bidder, to fund the construction and operation by Borrower and its subsidiaries of wireless networks using such licenses. …Cricket has made an equity investment of approximately $7.6 million in the Guarantor, comprising an 82.5 percent non-controlling membership.” US Cellular’s Form 8-K (September 22, 2006) reports that US Cellular has made capital contributions and advances to Barat Wireless of $79.9 million to provide initial funding of Barat’s participation in the AWS auctions and that US Cellular expects to make additional contributions to Barat. NextWave Telecom was founded in May 1995 (as the PCS auctions were being held),

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as the parent company of NextWave Personal Communications (PCI), NextWave Wireless and TELE*code Inc. NextWave PCI the successful bidder for 63 licenses in the PCS auctions, for a total of $4.7 billion dollars. After paying $500,000, in 1998, NextWave Telecom defaulted and filed for bankruptcy protection. The FCC repossessed the licenses and reauctioned them for nearly $16 billion. The US Court of Appeals for the District of Columbia Circuit ruled that the FCC had no right to cancel NextWave’s licenses and the U.S. Supreme Court upheld the lower court’s ruling that U.S. bankruptcy law precluded the government from revoking the licenses. In April 2004, the FCC and NextWave Telecom reached a settlement by which the FCC retained funds from the sale of seventeen percent of the spectrum to Cingular, seventy-two percent of the spectrum (1550 MHz of spectrum in 60 markets) was returned to the FCC, and NextWave retained ten percent (300 MHz of spectrum in 25 markets). In April 2005, NextWave Telecom reorganized and sold NextWave Telecom (and the PCS spectrum held by this entity) to Verizon for $3 billion. NextWave Wireless remains a corporate entity and AWS Wireless is a wholly owned subsidiary of NextWave Wireless. http://weblogs.jupiterresearch.com/analysts McDonough, C. (2008) op. cit. McDonough, C. (2007, February). The Impact of AWS on the Structure of the Wireless Telephony Industry. Paper presented at the 2007 Eastern Economics Association Conference, New York, New York. This spectrum will become available once these broadcasters switch to digital signals in February 2009. On February 1, 2008, an unidentified company bid $4.7 billion yesterday for the upper 700 MHz C block spectrum, exceeding the

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reserve price of $4.6 billion that triggered open-access rules. FCC website, Wireless, Auction 73. “FCC spells out rules for 700 MHz bands,” EE Times, 8/1/2007. Second Report and Order, 700 Mhz Bands, Federal Communications Commission, adopted July 31, 2007. The Grinnell Test examines (1) the possession of monopoly power in the relevant

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market and (2) the willful acquisition or maintenance of that power as distinguished from growth or … historic accident. (2001). Antitrust and the Information Age: Section 2 Monopolization Analyses in the New Economy. Harvard Law Review, 114, 5. WiFi technology is defined by IEEE Spec. 802.11. WiMax technology is defined by IEEE Spec. 802.16

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Chapter VI

Shaping Regulation in the Australian Mobile Industry Indrit Troshani University of Adelaide, Australia Sally Rao Hill University of Adelaide, Australia

Abstract The adoption and diffusion of mobile services has achieved a spectacular growth in many countries around the world. However, regulators in these countries are finding that existing regulatory frameworks are not suitable for dealing with these services. This chapter employs qualitative evidence to investigate how regulation and legislation can affect mobile services in the Australian mobile telecommunications industry and draws from it to propose an innovative regulatory framework. The framework is comprised of five major components: consumer and intellectual property protection, market and resources access, and environmental protection. We argue that these encompass the interests of the stakeholders operating in mobile industry and given its dynamic and complex nature co-regulation is an effective approach that can be used to minimize costs and enhance compliance.

INTRODUCTION With the advent of broadband wireless networks, the number of 3G subscribers is predicted to rise to nearly 800 million worldwide by the end of 2010 from 70.6 million recorded at the end of 2005 (Informa, 2005b). In addition, many markets have surpassed the 100% handset penetration and in those markets mobile users are attracted to new

and compelling mobile services (Mylonopoulos & Sideris, 2006; Steinbock, 2005). These market conditions provide a conducive environment for delivering increasingly sophisticated mobile services which constitute a substantial source of potential revenue growth for the stakeholders of the mobile telecommunications industry (Alahuhta, Ahola, & Hakala, 2005; Kumar, 2004; Massey, Khatri, & Ramesh, 2005).

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Shaping Regulation in the Australian Mobile Industry

A mobile service can be defined as an activity or series of intangible activities that occur when mobile consumers interact with systems or service provider employees with the support of a mobile telecommunications network (Bouwman, Haaker, & De Vos, 2007; Van De Kar, 2004). Examples of mobile services include mobile e-mail, SMS and MMS services, content downloads, mobile ticket reservations, mobile stock trading, and mobile TV (Bina & Giaglis, 2005). Mobile services are complex and require the integration of diverse technological and organizational resources which typically cannot be found within a single organization. Consequently, the knowledge necessary for developing and deploying these services may involve several heterogeneous stakeholders who are often embedded in various technological, economic, and social settings. In order to succeed, these stakeholders must interact with each other while complying with legal and societal requirements that balance their diverging interests, motivations, and needs (Camponovo & Pigneur, 2003). These requirements constitute a regulatory regime which, by definition, can operate at either industrial, national or international levels and can influence, direct, limit or prohibit any activity undertaken by stakeholders operating in the mobile industry (Yoo, Lyytinen, & Yang, 2005). Typically, regulatory regimes are set by regulatory and legislative authorities including government agencies, industry and consumer associations. Combined with the complexity of stakeholder interactions, regulation has the potential to affect the offerings and the uptake of mobile services (Kijl et al., 2005; Sangwan & Pau, 2005). Credible and transparent regulatory rules can boost investments in the industry, promote public confidence and the development of innovative and affordable mobile services while stimulating industry research and development efforts (Verikoukis et al., 2006). However, regulation can also impact the industry in a negative way. Increasing regulatory compliance fees for stakeholders can increase

the overall cost of operation well beyond that of acquiring the technology itself (Tongia, 2007). As the mobile services industry matures, it is attracting the attention of policy makers and consumer advocacy groups that are increasingly focusing on its regulation (Woolfson, 2005). MacInnes (2005) argues that when a service technology “has reached some minimum standard of performance and reliability one needs to be concerned with societal, legal, and general economic factors. This is a stage that is generally overlooked because it is not until a technology has been commercialized that the originators realize the problems that the technology poses to society in general. … A successful implementation of a business model around new technologies would have to consider those potential obstacles and provide solutions.” (p. 7). That is, solutions are needed for potential legal, societal, and general economic concerns that mobile services may introduce (MacInnes, 2005). Regulatory regimes around the globe are ill equipped for dealing with technologies such as mobile services because the “existing policy frameworks have been inherited from specific national, regional, and international histories of regulating broadcasting, telecommunications, and media, as distinct entities, and are not well-placed to deal with contemporary communications technologies that blur the boundaries among these.” (Goggin & Spurgeon, 2005, p. 181). Although limited studies about regulatory regimes are available in the literature they lack comprehensiveness (Li & McQueen, 2008; Oh et al., 2008; Tallberg et al., 2007; Buerkler, 2005; Grzybowski, 2005; Han et al., 2006; Jho, 2007). In fact, many scholars argue that research in this area is lacking (Gelenbe, 2003; Killström et al., 2006; Pitkänen, 2006; Ubacht, 2004). Further, practitioners believe that a healthy regulatory environment is essential for the growth of these industries (Chen, 2008; Hsieh, Jones, & Lin, 2008; Informa, 2005b, 2006a; Verikoukis et al., 2006; Woolfson, 2005; Goggin & Spurgeon, 2005). With this study, we

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attempt to address these concerns and the lack of vigorous research into regulatory frameworks. Our objective is to leverage on extant literature and use qualitative evidence collected to explore how regulation can affect the mobile industry. The study will culminate with a regulatory framework for the mobile services industry. The Australian mobile services industry was used as a setting for investigating this objective. This study is important for several reasons. First, it can be invaluable to stakeholders in the mobile industry in helping them improve their understanding of the environmental factors that enhance or constrain their positions in their value chain, and industry. A deeper understanding of such factors can help stakeholders in many ways in i) achieving a valuable competitive advantage. Stakeholders that exhibit compliance with regulatory rules that benefit users of mobile services may achieve their trust more effectively than those who do not (Killström et al., 2006); ii) providing stakeholders the opportunity to “achieve knowledge on legal issues, to stay away from legal areas in which processes are unclear, and to avoid related risks.” (Kijl, 2005, pp. 6667) which decreases potential transaction costs (Kijl et al., 2005; Woolfson, 2005); iii) helping Figure 1. The structure of Australian mobile industry

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avoid unbalanced legal rights amongst stakeholders which can severely threaten businesses by causing otherwise innovative business models to be illicit (Kijl et al., 2005; Killström et al., 2006; Woolfson, 2005). Second, regulatory and legislative influences can have direct implications on how mobile services and business models are designed and how they operate at organizational, industry and environmental levels. Further, these influences can determine the nature of mobile services that can be offered and their diffusion trajectories amongst end-users (MacInnes, 2005; Spiller & Zelner, 1997). This chapter is organized as follows. First, we overview the Australian mobile industry, then, we discuss the research method before elaborating the proposed regulatory framework. Finally, we conclude the paper and identify and future research directions.

THE AUSTRALIAN MOBILE INDUSTRY: AN OVERVIEW To set the scene, we provide a brief overview of the Australian mobile industry. The diagram in Figure 1 has been adapted from the work of

Shaping Regulation in the Australian Mobile Industry

Troshani and Rao (2007a) and summarises the current structure of the Australian mobile industry. To distribute mobile services to demand-side stakeholders, intense interactions need to occur amongst supply-side stakeholders. These occur in an environment which is being co-regulated by both the industry itself and facilitating stakeholders including the government regulator and various industry associations (Troshani & Rao, 2007a). The interactions that occur amongst supplyside stakeholders include mobile service development, marketing, distribution and billing. The roles of the major stakeholders shown in Figure 1 are briefly described in Table 1. A regulatory regime is meant to stimulate the changing market environment from monopoly to

competitiveness, protect consumers, but also to be reactive to market dynamics in order not to over- or under-regulate. On the one hand, overregulation can bring several adverse outcomes to the industry including, high engagement costs and possible duplicative and confusing rules for all stakeholders including end-users (AMTA, 2005a). On the other hand, under-regulation can also lead to adverse outcomes for the industry including unfair market dominance of players which may lead to uncompetitive conditions as well as end-user exposure to unfair and illicit trading practices. The relationship between the regulators, supply- and demand-side stakeholders should be dynamic, mutually responsive, and co-evolutionary, in that the regulatory authorities should match their activities to the issues that

Table 1. Categories of the stakeholders and their roles Mobile Network Carriers (also known as mobile network operators) supply a variety of telecommunication services to subscribers who use their network infrastructure. Typically, carriers own network infrastructures or hold licenses for spectrum allocations which are required for providing mobile services to subscribers. Carriers also establish technical support layers and generally have control over subscriber information and billing. This category also includes Mobile Virtual Network Operators (MVNO) which do not own their network infrastructure, but have business arrangements with carriers to buy minutes of use (MOU) to sell to their end-users. Accessibility/Connectivity Aggregators typically operate SMS gateway infrastructures that connect to many carrier networks. They purchase end-to-end mobile services from the carriers and act as an interface between these and service providers. Service Providers provide the technology platform for delivering mobile content to end-users by setting up SMS short codes which can be advertised and promoted through various media properties (e.g. TV and magazines). Content aggregator/publishers bundle content and services from multiple sources. They provide wider dissemination by negotiating intricate, complex and time-consuming agreements with network carriers. Content aggregators also provide mobile content platforms which integrate numerous content sources into a single interface for end-users. Content Intellectual Property (IP) owners/labels/content providers/media owners create original content from brands, traditional music, films, TV, games etc., and deliver it to consumers via network carriers, service providers or content aggregators. Application providers The availability of mobile services is supported by the work of application developers who employ industry development tools to create innovative applications for packaging content offerings. Industry Association - Content IP owners/labels/content providers are responsible for creating a framework for uniting dynamic and diverse industry stakeholders, hosting networking events, business forums, industry development programs, training sessions, advising government on policy development and promoting industry innovation. Industry Association - Carriers represents the mobile carriers that operate in Australia. They ensure that the mobile carrier industry as a whole addresses community and government expectations. They also coordinate the deployment of mobile networks, enhance communication and consultation among stakeholders, and liaise with government. Industry Association - Users represent end users and provide independent views on mobile telecommunications policy and service issues, including competition, regulation, end-user protection. Government Agency is responsible for promoting regulation and competition in the mobile telecommunications industry while protecting consumers. They also aim at creating an environment where community standards are respected and user concerns are addressed. Mobile Subscribers should be considered as a legitimate stakeholder in the mobile telecommunications industry, because their lives are likely to be affected by mobile services.

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themes (Cassell & Symon, 1994; Smith & Fischbacher, 2005; Yin, 1994). Qualitative empirical data were collected via semi-structured faceto-face interviews, which were used because of their flexibility. In-depth interviews provide rich insights for exploring, identifying, and understanding viewpoints, attitudes, and influences (Healy & Perry, 2000). Moreover, they also allow greater control over the interview situation (e.g. sequencing of questions) while providing the opportunity for making clarifications and collecting supplementary information (Frankfort-Nachmias & Nachmias, 1996). As indicated in the previous section, stakeholders of the mobile service industry can be categorized into eight groups – carriers, accessibility aggregators, content aggregators, service providers, content owners/providers, application providers, industry associations, and regulatory bodies. Industry associations can be broken down

arise due to the complex dynamics of the mobile market on an ongoing basis. The manner in which stakeholder interactions are influenced by the regulatory regime has direct implications on the mobile industry, and thus, constitutes the scope of this investigation the method of which is described next.

METHOD This chapter is exploratory in nature and utilizes qualitative evidence. We are concerned with the extent to which interpretations of regulation are sensible in the Australian context and the way in which these influence the adoption and diffusion of mobile services in Australia (Neuman, 2000). A qualitative exploratory approach enables the study of dynamic, intricate, and multifaceted processes as well as the exploration of emerging Table 2. Categories of stakeholders interviewed Interviewee Role

1

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Carrier

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8

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X

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X X

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21

X

X

X

X

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Service Provider

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Content Owner Application Developer Industry Association (Content Providers) Industry Association (Users)

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X

X

X

X X

X

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X

X

X

X

X

X

X

X

X

Industry Association (Carriers) Government Regulator

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Accessibility Aggregator Content Aggregator

11

X

X

X

X

X

X X

Shaping Regulation in the Australian Mobile Industry

further into user groups, content providers’ association and carriers’ association. The contact details of these organizations were obtained from the Australian Interactive Media Industry Association’s (AIMIA) and Australian Mobile Telecommunications Association’s (AMTA) websites and they were then approached by phone calls and emails. Twenty two key informant representatives of these organizations agreed to be interviewed. They were considered experts within their organizations on mobile services topics. One of the challenges in selecting participants was to have at least one representative from each stakeholder category so that the views of each stakeholder are taken into account. Some of the organizations that were interviewed carry out multiple roles in the industry as shown in Table 2. Figure 1 and Table 2 reveal that the sample of the interviews is generally representative of the Australian mobile telecommunications industry. Admittedly, we were unable to interview representatives from MVNOs. However, because the carriers occupy most of the market share in Australia lack of MVNO representation, though a limitation of the study, it cannot invalidate the qualitative findings reported in this paper (Informa, 2005a). The major carriers, their respective market shares, their growth prospects have been summarized in the Appendix to this paper. Also the Appendix includes the number of subscribers in Australia, the nature of the services used, the balance between prepaid and postpaid services and their growth prospects until 2010. The interviews were focused on the mobile industry stakeholders and their roles; their perceptions on existing regulation and its impact on their operations; lessons learnt and experiences, and future directions. The contents of the interview transcripts were analyzed thematically. Codes were developed which provided the basis for cross-case analysis and helped identify and analyze emerging patterns of themes (Carson et

al., 2001; Miles & Huberman, 1994). The themes were subsequently categorized and validated with existing literature before representative quotations were shortlisted from the interview for illustration purposes. We believe that construct validity has been adequately addressed. First, multiple sources of information were used (Yin, 1994). While interviews constitute the primary source of information, some of the informants provided supporting secondary data which is comprised of archival white papers, professional journal articles and press releases, and web resources. In addition, the investigators themselves identified additional supporting documentation including materials located at the websites of the informants’ organizations and industry publications. These secondary data were used for verifying and triangulating the findings of the interviews. Second, the informants belong to different categories of the mobile telecommunications industry. This ensured that different perspectives were provided which constitutes an important type of triangulation of qualitative information sources by preventing biased opinions (Choudhrie, Papazafeiropoulou, & Lee, 2003; Patton, 1990). Third, two investigators conducted and analyzed all interviews (Denzin, 1989). This kind of triangulation reduces the potential bias which is commonly cited as a limitation of interviews (Yin, 1994). Finally, the chain of evidence, tracing the conclusions to the interview summary and to the interview transcripts was also maintained. According to Yin (1994), these enhance the construct validity as well as the reliability of the research, thereby boosting its overall quality. Clearly, the study reported in this paper is based on the Australian context, and therefore, we accept its external validity cannot be ensured. Consequently, our findings may not be readily generalizable beyond this study (Shanks, Rouse, & Arnott, 1993). To ensure generalizability, further research is required, both in Australia and in other contexts.

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ANALYSIS In this section, we use the ideas presented in the work of (Kijl et al., 2005; Killström et al., 2006)) as a basis to analyze our findings. Specifically, we examine five major regulatory issues, namely, consumer and intellectual property protection, market and resources access, and environment protection. These and the manner in which they operate in the Australian context are discussed in detail in the sections that follow and they form the backbone of a regulatory framework which we propose later in the paper.

Consumer Protection Privacy is the right of individuals to be left alone and to exercise control over one’s personal information. Privacy includes information privacy which represents the way in which organizations handle an individual’s personal information (Minch, 2004; Newman & Bach, 2004; NgKruelle et al., 2001). Privacy has been one of the core issues in the internet environment and it has similar effect in the mobile context (Minch, 2004; Newman & Bach, 2004; Ng-Kruelle et al., 2001). All interviewees were consistent in indicating that their organizations have strict policy provisions in place for safeguarding the privacy of consumer information with some even having implemented encryption mechanisms. These provisions were consistent and compliant with Australia’s Privacy Act of which there was strong awareness amongst all interviewees (Ng-Kruelle et al., 2001). Privacy becomes particularly important with context-aware mobile services whereby information related to users’ context is collected. Ineffective regulatory conditions can be exploited by unethical market players that interface with end-users in an attempt to create unfair strategic advantage by using the end-users’ personal data (Ubacht, 2004). Consequently, the end-users’ perceived credibility and trust in the mobile environment can be adversely affected, particularly,

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if undesirable opportunistic behaviors occur (Rao & Troshani, 2007; Troshani & Rao Hill, 2008). Specific legislation and regulation is, therefore, required for safeguarding end-users’ rights of privacy (Figge, 2004; Minch, 2004). Interviewees also indicated that privacy regulation in the mobile industry has also considerably restricted the range of mobile services that are being offered in the Australian market. For example, Interviewee 7 describes Australian carriers to be “absolutely paranoid about privacy” which has affected the uptake of certain mobile services, including location-based services. In general, regulation can potentially be either a driver or a “big barrier” (Interviewee 7) for the diffusion of mobile services as captured in the following statement: … Australia’s prime supervisions of privacy … have a definite influence on the way that the mobile community has formed, because of what you can do in terms of marketing on a mobile phone, which is different in Europe. So of course they have services there that we don’t have here because their regulatory environment enables that. (Interviewee 1) Protection of Minors There was broad agreement amongst interviewees that policies and legislation should be in place for regulating the access of offensive and harmful mobile services and content including adult content, inappropriate gaming, and gambling services from minors. Although certain types of mobile services (e.g. adult and quasi-adult services), have been driving demand and generating substantial revenues for many supply-side stakeholders, the mobile industry is making efforts to provide these services responsibly into the Australian market (ACMA, 2006). In response to these concerns, the government regulator and industry have been collaborating to design measures for reviewing the applicability of regulation of content and services delivered to mobile phones. The first

Shaping Regulation in the Australian Mobile Industry

step towards the development of these measures is classification of mobile content and services (ACMA, 2006). Further, Australian carriers have taken initiatives for implementing robust access controls and age verification processes for restricted content in order to eliminate the possibility of minors accessing inappropriate services. In general, all stakeholders have been proactive in promoting the safety of minors in the mobile space (AMTA, 2006). The efforts of the Australian mobile industry have culminated with the new Restricted Access Systems Declaration (RASD) which places obligations on all supply-side stakeholders to subject offerings of mobile services including mobile portals and premium rate SMS/MMS services to age-restricted access rules (ACMA, 2007a, 2007b). Contractual Relationships refers to protecting the contractual bilateral relationships between supply- and demand-side stakeholders. This includes protecting end-users in their relationships with mobile network operators with mobile retail tariff regulation, mobile number portability, spamming, and product and billing disclosure (ACMA, 2006). Interviewees were consistent in their expectations that the government regulator should collaborate with industry to regulate these issues and create an industry code of conduct. Interviewee 11 argues that regulating these aspects is particularly important in the mobile industry which may be particularly susceptible to fraud. Interviewee 12 illustrates:

The devious activities of unscrupulous players in the mobile industry have a strong potential of creating mistrust, and in turn, seriously damage the reputation of legitimate supply-side stakeholders (Woolfson, 2005). A trusting environment is extremely important to exist in the industry for the mobile services to be widely adopted (Troshani & Rao Hill, 2008). According to the Australian Telecommunications Industry Ombudsman (TIO), mobile complaints represent approximately 43% of total complaints (ACMA, 2006; Informa, 2005b). In response to a dramatic increase in complaints about SMS-based premium services, such as ringtones and horoscope downloads, particularly, from young adults, and in collaboration with the regulator, Australian content providers have implemented the Mobile Premium Services Scheme. Under this scheme, content providers are required to indicate clearly whether automatic subscription is involved with any purchase and all associated costs (ACMA, 2007b). In addition, the government regulator has collaborated with the industry to issue guidelines governing mobile commerce practices which expect both mobile operators’ and content providers’ compliance. These guidelines aim to protect consumers from dubious marketing practices, and educate mobile content providers about their responsibilities concerning the disclosure of information on pricing, consumer contracts, and terms and conditions (Rao & Troshani, 2006).

Intellectual Property Protection [some content providers] are running ring tones and screen savers at the moment. They’re targeting the youth market. They send an SMS saying do you want a free ring tone. If you say yes, you’ve found that you haven’t just signed up for a free ring tone, you’ve signed up for a monthly subscription for twelve months for a ring tone at [A]$7 a month. This just turns up on your bill. This is destroying [consumer] trust and confidence. (Interviewee 12)

Refers the use of copyright, patent, trademark, digital rights management (DRM) and electronic licensing schemes for protecting intellectual property rights associated with mobile services provisioning. Effectively deployed DRM solutions create additional ways to generate revenue and ensure that both consumers and content developers trust the mobile channel. A key issue facing creators and distributors of mobile content

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Shaping Regulation in the Australian Mobile Industry

is protection from piracy and unauthorized use (Craig & Graham, 2003). In Australia, mobile content providers depend on the widespread adoption of DRM technologies and on the Intellectual Property Rights (IPR) regime (Liu, Safavi-Naini, & Sheppard, 2003; Rao & Troshani, 2006, 2007a, 2007b). All interviewees, content providers and application developers in particular, did recognize the threat that piracy poses to ownership rights. Although all expressed concerns about this phenomenon, many had accepted it as “fact of life” (Interviewee 22). Interviewees were, however, consistent in suggesting that intellectual property protection or lack thereof does influence the decision whether to use a channel for distributing their content or services. Most interviewees indicated that precautionary measures are undertaken independently intended at curtailing intellectual property violations. These include screening the trustworthiness of distribution channel partners and using technical solutions to curtail piracy.

Market Access Market access concerns with accessing markets with appropriate mobile frequencies and obtaining the required operational licenses. It also includes competition and antitrust legislation which is aimed at ensuring that competition is not distorted and, consequently, consumers receive quality mobile services. The mobile market is unique in the telecommunications domain. This is because licenses are technically and politically limited (Ubacht, 2004). Although licensing is meant to occur in a competitive manner, new carriers are not likely to be on equal footing with incumbent ones as the latter have advantageous starting positions due to prior well established presence and market power often through vertical integration with other industry players (Ubacht, 2004). Consequently, asymmetric market positions of the network operator players may become a source of regulatory concerns. Many interviewees

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argue that, currently, Australian supply-side stakeholders do not have equitable access to the market of mobile content and services, and that the government regulator should interfere by creating “a level playing field” (Interviewee 1) for all. Two main issues were raised: First, government favouritism for one of the mobile network operators has the potential to create monopolistic behaviour in the mobile market. The interviewees representing the carriers, in particular, argued that there should be market access regulation: The difficulty the government [regulator] has at the moment of their own design is that the government is the major shareholder in the largest telco in Australia (Interviewee 6) The carrier interviewees were consistent in arguing that this position of power of the government-owned operator has affected competition for market access: [The] key for companies such as ours is to make sure that where there’s predatory market behavior, the government and the regulator make sure that it’s not going to the detriment of competition. So if you look at - bundling is a big one for us and a lot of the smaller telcos, where companies like XXXXX can bundle, say you can bundle your home, your mobile, your business, your [cable/satellite TV], you can put them altogether and provide a discount. That’s monopolistic behavior which makes it very difficult for competition. (Interviewee 6) While there is no evidence that bundling strategies, as suggested above, have wielded substantial market power, strategies of this nature do have the potential of creating anti-competitive market domination of the larger operators over the smaller ones. Consequently, the Australian regulator will continue monitoring the market for further developments (ACMA, 2007b).

Shaping Regulation in the Australian Mobile Industry

Second, the non-operator supply-side stakeholders were generally consistent in arguing that there is a power imbalance between carriers and the remaining supply-side stakeholders. This was of concern to many because the fact that carriers control billing and customer relationships gives them “the upper hand” (Interviewee 2) in controlling revenue sharing schemes with content providers. In fact, these schemes were perceived by many to be “unfair”, thus, creating a “huge barrier” (Interviewee 2) for content providers. Nevertheless, the majority of the interviewees were consistent in indicating that revenue sharing should be dictated by competitive market dynamics rather than by regulatory intervention.

Resources Access Resources access includes knowledge development and deployment as well as subsidies provided by the government. These are discussed next. Knowledge Development and Deployment The creation of technical and business knowledge underlying the development of mobile content and services is essential for the success of emerging industries. Currently, many content providers such as digital media organizations, artists, musicians and film makers have exhibited a huge interest for distributing their content via the mobile channel, however, the knowledge concerning the ways that mobile content can be adequately formatted and commercialized for mobiles is limited. Funding research or coordinating taskforces that build this knowledge are two possible options for mobile industry stakeholders (Choudhrie, Papazafeiropoulou, & Lee, 2003; Damsgaard & Lyytinen, 2001; King et al., 1994). Currently, the content providers’ industry association in collaboration with government and a few key players in the industry have jointly undertaken active knowledge building steps, such as research, for developing this body of knowledge. Once built, development knowledge and technical know-how needs to be deployed and

this is important not only for building awareness amongst stakeholders, but also for showing them how business models operate. Interviewee 8 argues that many: …[supply-side stakeholders] do not understand the technology” and “there are very few points of contact where they [stakeholders] can be educated. (Interviewee 8) Therefore, industry associations should become more proactive in undertaking additional knowledge deployment measures including education and training. These measures can help supply-side stakeholders acquire the necessary knowledge and learn about the ways that they can format mobile content and services for mobile media, and distribute to end-users. As part of knowledge deployment the interviewees emphasized the need for publicizing success stories of exemplar local supply-side stakeholders in the local media and industry newsletters. This, they argue, is likely to create a conducive environment for the emergence of a social learning phenomenon based on the “law of imitation” (Hamblin, Miller, & Saxton, 1979). Publicized success stories set examples and could help new entrants in the industry learn about critical success factors and lessons learnt from past experiences. Interviewees were consistent in indicating that although there have been several success stories of local content providers in Australia, limited few have been widely publicized in local media. Subsidies Often governments, industry associations, and other powerful players in the market may provide subsidies to players in emerging industries (Choudhrie, Papazafeiropoulou, & Lee, 2003; Damsgaard & Lyytinen, 2001; King et al., 1994; Muzzi & Kautz, 2004). All interviewees indicated that currently, in the Australian mobile industry subsidies have mainly been in the form of small grants to fund trips to mobile fairs, exhibitions, and industry conferences to help small stakeholders showcase their products and facilitate

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Shaping Regulation in the Australian Mobile Industry

networking with key stakeholders. Also, industry associations such as AIMIA systematically provide free access to market intelligence (Mackay & Weidlich, 2007). However, many believe that this level of subsidy support is limited. Many stakeholders in the mobile industry, particularly, content providers and application developers, believe that they are in a disadvantaged position in Australia. First, they believe that there is a lack of risk-sharing in the Australian industry which hinders development. For example, developers of games and mobile TV episodes incur substantial development costs, but share revenues with carriers or aggregators (Interviewee 21). When mobile services fail to generate expected revenues, losses are borne solely by developers. Second, many interviewees indicated that current funding and incentive schemes are inadequate. They expect government and industry associations to help by funding innovative services, and research and development initiatives.

Environmental Protection Environmental protection is concerned with how developments in the mobile industry affect the environment. The Australian mobile industry has undertaken a transparent, viable and sustainable mobile phone recycling campaign with the objective of preventing used mobile phones, accessories and batteries end up in landfill and as a result minimize environmental burden (AMTA, 2006). With increasing handset replacement rates (Informa, 2005a, 2005b), most interviewees support the mobile phone recycling campaign and hope that this initiative will start a bandwagon effect amongst all stakeholders.

REGULATORY FRAMEWORK FOR MOBILE SERVICES In general, regulation setting is implemented by organizations with legislative powers, such as reg-

98

ulatory bodies. These regulate the context in which products or services are developed, deployed, and used. For emerging industries such as the mobile services industry, regulatory authorities have to deal with a multitude of heterogeneous networked stakeholders. Further, as mobile technology operates in a dynamic environment and undergoes rapid changes, regulatory definitions become a moving target which implies that regulators should constantly acquire industry-specific knowledge over time (Tallberg et al., 2007; Ubacht, 2004). Consequently, regulation for the mobile industry becomes an extremely complex and involved undertaking for all stakeholders. The Australian government policy for the mobile industry is characterized by a co-regulation approach which represents close collaboration with the industry in terms of a mixture of direct intervention through legislation, on the one hand, and complete self-regulation on the other. There is no direct regulation, but also there is no pure self-regulation. Regulatory bodies provide the industry with some parameters concerning the regulatory issues discussed in the previous section in which key problems are to be solved. It is the responsibility of the industry to work out the details that best suits mobile technology and related business models. The role of the regulator is thus to allow the industry to apply its own codes in the first instance and to monitor the effectiveness and enforcement of those codes (AMTA, 2005a). The diagram in Figure 2 integrates the regulatory issues discussed previously with the notion of co-regulation to form our regulatory framework for the mobile industry in Australia. These issues are feasible for two reasons. First, they were presented by the interviewees and feature heavily in the literature as important prerequisites for the success of the mobile industry. Second, these issues have been implemented in various forms in other industries. These issues fit together in the framework in that they represent the interests of all stakeholders and are shaped by their joint

Shaping Regulation in the Australian Mobile Industry

Figure 2. Co-regulation in the mobile industry in Australia Supply-side stakeholders

Demand-side stakeholders Regulatory & legislative context - Consumer protection - IP protection - Market access - Resource access - Environment protection

Framework development

Framework operation

Facilitating stakeholders

Regulatory Monitoring

Regulatory Intervention

Mobile Telecommunications Business Models

efforts. For example, while consumer protection is geared towards protecting end-users, market access protects smaller or weaker supply-side stakeholders against predatory practices of more powerful ones. As indicated in Figure 2, the consideration of these issues is made by involving the industry as a whole instead of individual stakeholders which is likely to result in balanced and sustainable outcomes in the long term. Figure 2 also shows that the regulatory framework operates via compliance monitoring and intervention. First, monitoring may be implemented by establishing suitable reporting mechanisms. Second, intervention should only occur in cases of compliance violations or market failure. Regulatory issues included in our framework, while jointly developed by all stakeholders, they do represent different but equally important stakeholders. Consequently, these issues are generally similarly equal in importance and complementary. It follows that their interaction is

likely to be frictionless. However, if conflicts do occur, facilitating stakeholders should intervene. In any case, the development and operation of the proposed regulatory framework should not interfere with or distort future market or industry developments. With co-regulation, the mobile industry is empowered and takes responsibility for participating in the development of its own regulation. Three major benefits emerge with this approach: first, regulation costs are likely to be significantly reduced; second, compliance is likely to occur naturally, and therefore, regulation in itself is likely to be perceived to be less restrictive and onerous than in traditional regulation models (ACMA, 2006; AMTA, 2006); third, industry-driven coregulation also has the advantage to ensure that it is likely to remain appropriate and be responsive to changing market conditions and capable of delivering timely and transparent outcomes. Taken together these advantages are likely to promote

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Shaping Regulation in the Australian Mobile Industry

business activity, market integrity, and investor confidence in the Australian telecommunications industry and its international competitiveness.

CONCLUSION AND FUTURE RESEARCH Regulating the mobile services industry is an extremely difficult task. There are many reasons for this, including the highly complex nature of the networks and stakeholder relationships required to provide mobile services as well as the constantly evolving underlying technologies. There are growing calls from both scholars and practitioners alike for further research in this area. In response to these calls we have conducted a study which draws both on existing literature and qualitative evidence and have proposed a regulatory framework for mobile services. We have first provided an overview of the Australian mobile services industry which was used as a setting for our investigation. We have subsequently discussed the research method followed by an elaboration of the proposed framework. We believe that this framework is the first of its kind, and, thus, it contributes to the existing body of knowledge which can be employed by both academics and practitioners alike. The framework is comprised of five major components: first, consumer protection including privacy, protection of minors, contractual relationships, second, intellectual property protection, third, market access, fourth, resources access including knowledge development and deployment, and subsidies, and finally, environmental protection. We argue that these encompass the interests of all stakeholders operating mobile industry and given its dynamic and complex nature co-regulation is the most effective approach to minimize costs and enhance compliance. Using our framework as a starting point, there are several directions for future research. First, the proposed framework may not be exhaustive.

100

Thus, further studies encompassing both wealthy and low income countries that can enable generalizations and further validation of the proposed framework should be undertaken. Second, further work should focus on enforcement mechanisms of the components of the framework. Third, different countries represent different regulatory jurisdictions which can be diverse (Verikoukis et al., 2006). As various supply-side stakeholders (e.g. network operators) increasingly offer mobile services across national borders, further research is required for developing regulatory interfaces for transnational mobile markets. This is an important first step for providing regionally or internationally unified regulation, thereby, increasing the current limited investment possibilities that exist in fragmented markets. Fourth, mobile communication platforms, services, content and devices are converging and changing rapidly. The challenge for both academics and practitioners alike is to investigate whether and how convergent and dynamic mobile services can be regulated without succumbing to the supposition that these constitute new problems requiring new regulatory solutions. Therefore, the question if regulation can be ‘technologically-neutral’ requires further investigation.

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Shaping Regulation in the Australian Mobile Industry

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Key Terms Contractual Relationships: Contractual Relationships refer to protecting the contractual bilateral relationships between supply- and demand-side stakeholders. This includes protecting end-users in their relationships with mobile network operators with mobile retail tariff regulation, mobile number portability, and product and billing disclosure. Co-Regulation: Co-regulation represents a regulation approach by way of which government regulations collaborate closely with the industry in terms of a mixture of direct intervention through legislation on the one hand, and complete selfregulation on the other. Environmental Protection: Environmental protection is concerned with how developments in the mobile industry affect the environment. Intellectual Property Protection: Intellectual Property Protection refers the use of copyright, patent, trademark, digital rights management (DRM) and electronic licensing schemes for protecting intellectual property rights associated with mobile services provisioning. Market Access: Market Access is concerned with accessing markets with appropriate mobile frequencies and obtaining the required operational licenses. It also includes competition and antitrust legislation which is aimed at ensuring that competition is not distorted and, as a consequence, consumers receive quality mobile services. Mobile Services: A mobile service is an activity or series of intangible activities that occur when mobile consumers interact with systems or service provider employees with the support of a mobile telecommunications network (Bouwman, Haaker, & De Vos, 2007; Van De Kar, 2004). Examples of mobile services include mobile e-mail, SMS/MMS services, content downloads, mobile ticket reservations, and mobile TV.

Shaping Regulation in the Australian Mobile Industry

Privacy: Privacy is the right of individuals to be left alone and to exercise control over one’s personal information. Privacy includes information privacy which represents the way in which organizations handle an individual’s personal information.

Regulatory Regime: A regulatory regime represents any type of authority which can operate at either industrial, national or international levels and which can influence, direct, limit or prohibit any activity undertaken by any stakeholder operating in the mobile telecommunications industry (Yoo, Lyytinen, & Yang, 2005).

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Appendix Table 1a. Australian Mobile Market to 2010 (Source: Informa, Global Mobile Forecasts to 2010) 2006

2007

2008

2009

2010

19,964

20,699

21,294

21,781

22,184

5.10

3.68

2.87

2.29

1.85

Penetration (%)

98.11

100.89

102.96

104.49

105.62

Total Revenues (US$ million)

8,885

9,138

9,195

9,075

8,869

5.04

4.59

4.33

3.90

3.81

Voice

7,627

7,650

7,474

7,121

6,673

Data

1,258

1,488

1,722

1,954

2,196

Voice

85.84

83.72

81.28

78.47

75.24

Data

14.16

16.28

18.28

21.53

24.76

8,739

9,173

9,524

9,811

10,049

44

44

45

45

45

Telstra Mobile

8,994

9,265

9,503

9,698

9,859

SingTel Optus

6,859

6,942

7,061

7,158

7,239

Total Subscriptions (000) Growth Subscriptions (%)

Growth Revenues (%)

Revenues (US$ million)

Revenue share (%)

Prepaid Total prepaid subscriptions (000) Prepaid as % of total subscriptions

Subscriptions by operator (000)

Vodafone

2,707

2,883

3,002

3,099

3,180

Hutchison (Orange and 3 Australia

1,404

1,609

1,728

1,826

1,906

Telstra Mobile

45

45

45

45

44

SingTel Optus

34

34

33

33

33

Vodafone

14

14

14

14

14

7

8

8

8

9

Operator market share (%)

Hutchison (Organge & 3 Australia)

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Section II

Telecommunications Industry

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Chapter VII

Analyzing the Disruptive Potential in the Telecommunications Industry Stefan Hüsig University of Regensburg, Germany

Abstract This chapter covers an important issue in the area of telecommunications planning and technology management: The ex ante analysis of potential disruptive technologies. Due to the convergence of IT and telecommunications, an ever-growing onslaught of emerging technologies and new entrants with new business models are starting to eat up the incumbent’s revenues, profits, and market shares. The theory of disruptive technology (Christensen, 1997; Christensen & Raynor, 2003) helps managers, policy-makers and analysts to analyze emerging technologies, new business models, and new entrants in order to be prepared in advance, providing appropriate ways to react in a timely fashion to innovation-based opportunities or threats. In this chapter the theory of disruptive technology, the concept of disruptive potential and a method for applying this concept in a telecommunications planning and technology management context is presented. Finally, some examples of potential disruptive technologies in telecommunication which were analyzed ex ante are introduced with specific emphasis placed on the WLAN-technology.

Introduction The telecommunications industry has been undergoing a radical transformation since the beginning of the new century, creating new opportunities and new challenges for infrastructure and service

providers (Christensen, Anthony, & Roth, 2004; Lia & Whalleyb, 2002). The formerly established integrated value chain is increasingly being deconstructed, industry borders are becoming increasingly blurred due to convergence between the Internet and telecommunications industry is

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Analyzing the Disruptive Potential in the Telecommunications Industry

being radically restructured with the entry of new players (Bores, Saurina, & Torres, 2003; Lia & Whalleyb, 2002). Unexpectedly, discontinuous technological developments in various areas of the industry and increasing market turbulence have added new dimensions to an already complex scenario. Many traditional business models, as well as related frameworks, tools, and methods have become obsolete. Therefore, the development of new conceptual frameworks for understanding these changes in the telecommunications and related industries; and the creation of new tools and methods for identifying opportunities and threats, and making new strategies is becoming a central task for academia. In the new environment of uncertainty and ambiguity managers, policymakers, researchers and analysts are in need of improved and new theoretical based frameworks to gather and interpret information in another way to finally recognize the opportunities and threats emerging from discontinuities faster and more effectively. So far the industries’ track record in innovation is quite mixed with 3G and the mobile Internet, Multimedia Messaging Service (MMS) or the attempts to transfer i-Mode to other contexts than Japan (Christensen et al., 2004; Hüsig et al., 2005; Lyytinen & King, 2002; Rao, Angelov, & Nov, 2006). Quite frequently innovations from outside the inner domain of the telecommunication industry are introduced by outsiders like Skype with Voice over Internet Protocol (VoIP) or Cisco Systems with their IP-routers which took and take away customers and revenues from the traditional incumbents in telecommunications (Christensen et al., 2004; Rao et al., 2006). Some traditional infrastructure suppliers in the telecommunication industry like Siemens or IBM already went almost completely out of this business with their circuitswitched technologies which were disrupted away by Cisco Systems – a new entrant with a new technology which the incumbents never managed to adopt effectively (Christensen et al., 2004). It seems that managers and analysts in telecom-

munications need better tools and methods to effectively identify and counteract disruptions like these. The theory of disruptive technology (Christensen, 1997; Christensen & Raynor, 2003) helps managers, policy-makers and analysts to analyze emerging technologies, new business models, and new entrants in order to be prepared in advance, providing appropriate ways to react in a timely fashion to innovation-based opportunities or threats. However, not many scholars have tried to apply this theory to the field of telecommunications (Christensen et al., 2004; Hüsig et al., 2005; Osterwalder, Ondrus, & Pigneur, 2005; Rao et al., 2006). Therefore, a more comprehensive and easily applicable method for identifying disruptive technology threats from an ex ante perspective had to be developed further, and is elaborated here. For managers, policy-makers and analysts in telecommunications a more applied version of the theory of disruptive technology in form of recently developed tool provides a better guideline for this important issue in the area of telecommunications planning and technology management. In this chapter, we present first the disruptive technology theory, then the concept of disruptive potential, and a method of applying this concept in a telecommunications planning and technology management context. Finally, some examples of potential disruptive technologies in telecommunication which were analyzed ex ante are introduced with specific emphasis placed on the WLAN-technology.

The Concept of Disruptive Potential The Disruptive Technology Theory In order to grasp the concept of disruptive potential it is essential to understand the theoretical underpinning first: The disruptive technology theory. The theory of disruptive technology or disruptive

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Analyzing the Disruptive Potential in the Telecommunications Industry

innovation originally came from Christensen’s research into the rigid disk drive industry (Christensen, 1993; 1997). His research focused on the question of why and under which circumstances flourishing incumbents in a given industry could be successfully attacked by new entrants using new technologies. He identified a specific set of such technologies with distinct characteristics, which he termed “disruptive” technologies. Accordingly, these disruptive technologies are defined as technologies which disrupt an established trajectory of performance improvement downwards, or redefine what performance means (Christensen & Bower, 1996). They stand in contrast to sustaining technologies, which are technological changes that have a sustaining impact on an established trajectory of performance improvement and give the known customers more and better versions of what they have valued up to now. These sustaining technologies lead to innovations that allow the firms to provide better and more profitable products to their existing customers (Christensen et al., 2004). Christensen’s findings indicated that incumbent firms almost always ultimately master these sustaining innovations but are often unable to cope with disruptive ones. Even though disruptive technologies initially underperform established ones in serving the mainstream market, they eventually displace the established technologies (Danneels, 2004) Christensen et al. (2004) differentiate two distinct types of disruptive opportunity: The “new-market disruption”, in which a disruptive technology does not compete with other existing products but instead competes against non-consumption and therefore establishes an entirely new market, or the “low-end disruption” where a disruptive technology can be used to attack an existing value network from the low end by deploying a business model that profitably serves the less demanding customers whom incumbent market leaders are happy to shed as they themselves concentrate on more attractive customers.

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Nevertheless, in the long run the initially inferior disruptive technologies from new markets or the low end typically introduced by new entrants become good enough to meet the demands of the mainstream customers of the incumbents, so that the incumbents are forced toward higher margin customer groups, or out of the market entirely. This process of disruptive and sustaining technological change is best illustrated by Figure 1 below. It is important to understand that Christensen defines the term technology quite broadly as “the processes by which an organisation transforms labour, capital, materials, and information into products and services” (Christensen, 1997; xiii). His process-based concept of technology extends beyond the engineering and manufacturing functions of the firm to also include business processes. Changes in these processes are innovations. Therefore, in his more recent publications the term “disruptive technology” (broadly understood) is now exchanged by “disruptive innovation” (Christensen et al., 2004; Christensen & Raynor, 2003). This means that Christensen’s concept of technology is not limited to physical products but is explicitly appropriate for a service-based industry like telecommunications. A disruptive innovation is typically financially unattractive for the leading incumbent to pursue, relative to its profit model and relative to other investments competing for the organization’s resources. This translates to an advantage for entrants which operate with an alternative business model and do not have similar trade-offs between sustaining and disruptive technologies, since they would focus on the disruptive technology in a market segment which is new or unattractive to the incumbent. Therefore, disruptiveness is not an absolute phenomenon but a relative one which can only be measured relative to the business model of another firm. In other words, an innovation that is disruptive relative to the business model of one firm can be sustaining compared to the business model of another (Christensen et al., 2004).

Analyzing the Disruptive Potential in the Telecommunications Industry

Figure 1. The process of disruptive and sustaining technological change in a given value network (Christensen et al., 2004; Christensen & Raynor, 2003)

The example of Voice over Internet Protocol (VoIP) can illustrate the relativity of the same technology used in sustaining or disruptive ways: VoIP could be used in a sustaining way to lower costs and add new high-value services by the incumbents without altering much of their traditional business model. On the other hand, entrants like Skype used VoIP to provide lower quality voice services for free in their network to enter the value network of the traditional telecom incumbents from the low end (Christensen et al., 2004; Rao et al., 2006). Providing lower quality services for free was not in the business model of traditional incumbents therefore they had initially little reason to change. Used with Skype’s business model, VoIP had more disruptive potential than in combination with the traditional model of the incumbents (Osterwalder et al., 2005). This case shows that almost the same technology can lead to a sustaining and disruptive outcome. Therefore the context, especially the value network and the specific business models have to be taken into account. The explanation for the incumbents’ behavior can be seen predominantly in the power of the

established customers in the mainstream market (Christensen & Bower, 1996). According to Christensen, the inability to change strategy at the right time and allocate sufficient resources to the new technology for the emerging market results in the interaction between distinct circumstances in the internal resource allocation process of the firm (Bower, 1970; Burgelman, 1983a, 1983b). This effect is also suggested by resource dependence theory as developed by Pfeffer and Salancik (1978). According to this theory, the strategies firms can choose are strongly restricted by the interests of their existing customers and investors, who provide the resources necessary to survive. Therefore, established firms allocate their resources to sustaining technologies that address the interests of their existing customers rather than to disruptive technologies about which the customers and markets are highly uncertain, and which are initially structurally unattractive (Christensen, 1997; Christensen & Bower, 1996). The failure of the incumbent firms concerning disruptive technologies is based not on a deficiency in technological competence but on the firms’ inability to change their strategy

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Analyzing the Disruptive Potential in the Telecommunications Industry

towards new value networks when there is little or no impetus from their existing and most valuable customers. The contrasting capabilities and asymmetrical motivations of incumbents and entrants in the face of disruptive technological change are based on different sets of resources, organizational processes, and values embedded in the organization’s culture which are formed over time by their surrounding value networks (Christensen, 1997; Christensen et al., 2004; Christensen & Raynor, 2003; Christensen & Rosenbloom, 1995; Overdorf & Christensen, 2000).

Critique and Advancement of Christensen’s Disruptive Technology Theory With the growing popularity of Christensen’s disruptive technology theory, the amount of criticism and extensions in the academic literature also increased. However, one must be careful when reading many of these papers, even if they have a scholarly source. Due to the complex argument of Christensen’s theory, not all his critics fully grasp the entire complexity of the reasoning and come to misleading results. Nevertheless, it is also important to be aware of the limits of the theoretical framework in order to apply the following method successfully in a real life setting. Therefore, an overview of the most important and valid criticisms and advancements are briefly presented here: •

•

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The theory still lacks terminological clarity and has methodological as well as formal deficits (Adner, 2002; Danneels, 2004; Govindarajan & Kopalle, 2006a, 2006b; Hüsig et al., 2005) The influence of institutional factors is still underdeveloped but might be important for the application and explanatory power of the theory especially in non-US contexts (Chesbrough, 1999, 2003; Hüsig, Dowling, & Hipp, 2007).

•

•

•

The explanatory power via the resource allocation process and the resource dependence theory was questioned as the effects of threat perception might lead to different rigidities and resource commitments inside the incumbents as reactions to potentially disruptive technologies (Gilbert, 2002, 2005; Gilbert & Bower, 2002). The influence of specific industry and technological contexts such as standards, lock-in-effects and network externalities on the disruption process is still not fully understood nor has it been researched in depth (Adner & Levinthal, 2001; Hüsig et al., 2005). The explanatory power of previously marginal product attributes, which, Christensen suggests, explain the adoption of the disruptive technology in the mainstream market, has been attacked by empirical reconsideration of the original data, suggesting that the role of the lower unit price of disruptive technologies when invading the established market is a prominent force to explain and forecast the phenomenon (Adner, 2002).

Some of these aspects could make it quite difficult to analyze the telecommunications sector using this theory as network effects, regulation, and scarce resources (e.g. frequencies) often play an important role in the adoption and diffusion of new services and technologies (Hüsig et al., 2005; Mannings & Cosier, 2001; Schoder, 2000). However, recent research in the telecommunications sector using the disruptive innovation framework shows the feasibility of the theory in this industry (Christensen et al., 2004; Hüsig et al., 2007; 2005). It seems that the incumbents in highly interdependent, networked industries provide better avenues for co-option (Christensen et al., 2004; Hüsig et al., 2005). In the case of telecommunications incumbents are often more motivated to fight the attack of an entrant building or acquiring the potential disruptive innovations

Analyzing the Disruptive Potential in the Telecommunications Industry

themselves. The exit from low-end markets in scale intensive and high fix costs industries like telecommunications might be less attractive than in other industries where attractive high end markets also provide higher profits and margins for the ceding incumbents. Nevertheless, also here the theory of disruption helps to explain and predict under which circumstances the likelihood for co-option or ceding of the incumbents would be higher or lower.

Analysis of Emerging Technologies Using the Concept of Disruption In a real life context, ex post reasoning is of little value to practitioners. They are more interested in an ex ante perspective in order to identify disruptive technological threats or opportunities to be able to formulate and implement a timely strategy. The concept of disruptive potential addresses this problem (Hüsig et al., 2005; Rafii & Kampas, 2002). Disruptive potential is a concept and measure for the ex ante analysis of the potential of emerging technologies for reaching the end of

the disruption process successfully. The degree of disruptive potential is measured by the relative amount of disruptive characteristics fulfilled. The result gives an indication of how threatening the potentially disruptive technology is likely to be at a given time. In order to grasp this concept fully, one must be clear that the disruption phenomenon is a longterm process which can be divided into different phases (Christensen et al., 2004; Hüsig et al., 2005; Rafii & Kampas, 2002). As long as the disruption process is not completed, the monitored technologies might have different degrees of disruptive potential but the final outcome remains unclear until the end. Therefore, it might be misleading to measure disruptiveness of innovations, since disruption is an output condition or variable and not an input set of attributes per se. It might be of academic interest to find out how complete the victory of the entrants with the disruptive technology is, but that has few implications for an ex ante analysis when the disruption process is still in progress. For enhanced understanding

Figure 2. The phases of disruption – here in phase 7; The other six phases have already been successfully undergone by the entrant Phase 1: Invention

Phase 8: Incumbent Displacement

Phase of Disruptive Process: 6/8

Phase 2: Innovation

Phase 3: Emerging Market Entry

Phase 7: Incumbent Retaliation

Phase 6: Customer Switching

Phase 4: Main Market Entry

Phase 5: Customer Attraction

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Analyzing the Disruptive Potential in the Telecommunications Industry

the phases of disruption are described below and shown in Figure 2. In Phase 1 the invention of the new technology with disruptive potential must be completed. Usually, technologies with disruptive potential are straightforward and the invention is at the architectural level (Christensen, 1992; 1997). Without an invention, no innovation whatsoever can follow. This frequently happens in the labs of the incumbents, who are characteristically unable to commercialize a potentially disruptive technology (Christensen, 1997). The first successful innovation phase is often carried out by some new firm that identifies a new untapped market need, or application by trail and error, which leads to Phase 2. The entrant’s successful entry into an emerging market represents Phase 3. If the entrant can establish itself in this emerging market niche, it gains a beachhead to enter the mainstream market of the incumbent. If barriers of entry can be conquered effectively, the fourth stage of the disruption process has been reached. Now the entrant attracts customers away from the incumbent with typically lower unit prices and good enough performance features, which requires overcoming switching costs of the mainstream customers. In Phase 7 the incumbent starts to feel the loss and has the option of retaliation. If the counterattack remains unsuccessful due to the wrong set of resources, processes, and/or values in the changed context and is unable to develop or acquire them, the victory of the entrant with the alternative technology is complete (Christensen & Raynor, 2003; Overdorf & Christensen, 2000). With the total displacement of the incumbent in the market leader position by the entrant, the disruption is finalized in Phase 8. After this phase the disruptiveness of the process might be measured to determine how absolutely and completely the incumbents and their technology have been substituted. Two other aspects should be considered when the concept of disruptive potential is used as a measure for ex ante analysis of the potential of

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emerging technologies to reach the end of the disruption process successfully. Due to the multiple uncertainties during this long-term development, the concept of disruptive potential must be seen as a heuristic concept that is based on historical analogies and pattern matching rather than primary number-driven quantitative analysis (Hüsig et al., 2007). Additionally, the disruptive potential of a technology can change over time depending on complementary innovations like business models. Therefore, the disruptive potential does not have a value that remains fixed over time, but needs to be reevaluated and permanently updated. These activities need to be embedded in a systematic innovation management process. In the next section it is elaborated on what such a management process and method for analyzing disruptive potential could look like.

Management Process and Methodology to Analyze the Disruptive Potential It is important to be able to distinguish between sustaining or disruptive technologies because of the different management actions which have to be taken in both cases. Unfortunately, as Christensen points out throughout his publications, it is not always easy to apply the categories of disruptive and sustaining innovation in practice: “Even people who deeply understood the theories [of disruptive innovation] struggled to use them in a repeatable and methodical fashion” (Christensen et al., 2004). Some of these difficulties might be due to the lack of terminological clarity, or methodological and formal deficits. One other reason for these difficulties is the fact that “disruption is a relative term” (Christensen & Raynor, 2003). This means that even though a particular innovation is disruptive to one player in an industry, it might be sustaining to another. This implies that firms have to be careful when categorizing innovations, particularly if most companies and

Analyzing the Disruptive Potential in the Telecommunications Industry

public opinion consider an innovation to be of a disruptive nature. It highly depends on the individual strategy and business model of each firm, their resources, processes, and values. Moreover, from an ex ante perspective there is the problem of technological and market uncertainty (Hüsig et al., 2005). To forecast the likelihood of disruption it is necessary to estimate the rate of technological progress for the performance supplied by the potentially disruptive technology and the technology in danger of disruption (Christensen, 1997). The market uncertainty inherent in the emergence of new sub-markets makes forecasts of potential customers, market growth, and size, or even useful applications of the potentially disruptive technology, very difficult (Chesbrough, 2003; Christensen, 1997). However, even with all of these limitations in mind the concept of disruptive potential can add more orientation in this uncertain and complex undertaking which needs to be improved, comparing it with the former track record of innovation and technology forecasting in the telecommunications industry (Chandler, 1999; Christensen et al., 2004; Hüsig et al., 2005; Schoder, 2000). Given the high market and technology uncertainty in disruptive circumstances, most approaches provide mostly qualitative and heuristic methods like those pre-

sented by Christensen et al. (2004), Hüsig et al. (2005), or Rafii and Kampas (2002). Typically, the favored methodical basis for the approaches given in the literature so far consists mainly of checklists with indicators, scoring models, and trajectory mapping. As long as there is no comprehensive and easily applicable methodology to identify disruptive technologies from an ex ante perspective, the danger of misinterpretation and oversimplification will persist in practice. Therefore, in the following one methodology for analyzing the disruptive potential based on Christensen’s research and the complements suggested by Adner (2002) to improve the precision of the disruptive technology concept and its usability for identification and forecasting developed by Hüsig et al. (2005) is presented together with a few improvements here. This approach helps managers, policy-makers and analysts to understand Christensen’s theory better and to enable them to apply the insight more easily in the difficult task of identifying potentially disruptive technologies. The method for estimating the disruptive potential of emerging technologies developed by Hüsig et al. (2005) must be embedded in a broader analysis and management process for disruptive innovations, which is shown in Figure 3. This

Figure 3. Analysis and management process for disruptive innovations (Hüsig et al., 2005)

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Analyzing the Disruptive Potential in the Telecommunications Industry

method was developed to support the first phase of this process: Disruptive technology scanning. After the disruptive potential is estimated in the first phase, more specific managerial actions can be taken in the second and third phases if the disruptive potential has been shown to be high. In this article we will concentrate on the first phase, in which the disruptive potential is primarily analyzed. The first step in this methodology is to define the current value network. The concept of the value network is described as the context within which a firm identifies and responds to customer needs, solves problems, procures input, reacts to competitors, and strives for profit (Christensen & Rosenbloom, 1995). Within such a value network, each firm’s competitive strategy, and particularly its past choices of markets, determine its perceptions of the economic value of a new technology. These perceptions shape the rewards different firms expect to reap through the pursuit of sustaining and disruptive technologies. In established firms, expected rewards, in their turn, drive the allocation of resources towards sustaining technologies and away from disruptive ones. Inside a value network, the way value is measured differs across the network. Through their unique rank ordering of the importance of various product or service performance attributes, the metrics of value define in part the boundaries of the value network. These metrics of value can be used to develop the dimensions for the trajectory mapping in the manner of Figure 1. From a practitioner’s perspective, the next question to be dealt with is the timeframe of the trajectory mapping. Since all factors influencing the firm are subject to certain conditions at a certain time, a planning and forecasting horizon has to be set for an appropriate analysis of the trajectories of performance improvement. In the case of disruption processes a longer time frame (at least the life-span of the potential disruptive technology) needs to be considered.

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Subsequently, cost structures and business models of the incumbents must be analyzed and understood. Typically, the business models of the incumbents in a traditional industry like telecommunications do not differ too much from each other; therefore an “average” incumbent could be taken. For the individual analysis of the impact of a potential disruptive technology on a specific incumbent the subject of analysis is clear – and a deeper analysis of resources, values and processes is more likely to be feasible. Then the technology with potentially disruptive characteristics is evaluated in connection with the current value network. Depending on the stage of the disruption process, further elements of the emerging value network of the entrant can also be analyzed. To support this evaluation a number of consistent characteristics were extracted that typically indicate the threat of disruption and presented in a questionnaire. This questionnaire was further developed into a checklist containing the main indicators to analyze the disruptive potential (see Table 2). Often selecting an interdisciplinary sample of experts is suggested to ensure that both the market and technological views are covered (Hüsig et al., 2005). Others suggest to combine the analysis of potential disruption with other forecasting methods like using a large sample of experts via a Delphi study or use Business Model Ontologys (BMO) to compare the different player’s business models (Osterwalder et al., 2005). It might also be helpful to complement the interview data with workshops, group discussions and additional studies to enhance the information basis of the analysis. Then all available information must be used to make decisions on the disruptive characteristics if possible. This task, the interviews and the moderating of the workshops should be performed by an expert in disruptive technology theory. In the approach of Hüsig et al. (2005) the disruptive potential is measured by the relative number of disruptive characteristics fulfilled. Since this

Analyzing the Disruptive Potential in the Telecommunications Industry

is simply a qualitative heuristic approach, more accuracy would seem rather misleading at this point. The results of the characteristics analyzed (yes = disruptive characteristics can be identified, no = disruptive characteristics cannot be identified, unknown = disruptive characteristics cannot be evaluated) should provide an estimate of how threatening the potentially disruptive technology is likely to be. In comparison with the method of Rafii & Kampas (2002) in which the factors can be rated on a seven-point scale that rates each contributing factor’s disruptiveness, here no average positions can be taken or must be declared as unknown. The relative numbers of fulfilled disruptive characteristics equal the degree of the disruptive potential of the technology analyzed. The relative numbers of unknown disruptive characteristics equal the degree of uncertainty on the disruptive potential of the technology analyzed. The more advanced the disruption process is, the lower the degree of uncertainty concerning the disruptive potential of the analyzed technology might be, and vice versa. This forecasting method is intended as a guideline for managers who are already familiar with Christensen’s theory, and to support guided interviews with experts to gather and analyze the necessary facts in a structured way. The value added of this method is to help practitioners render the process of analyzing disruptive potential more systematic and comprehensive. Therefore, a more structural approach should also improve the quality of forecasting outcomes, especially if the number of the interdisciplinary experts using the proposed method grows and an aggregated analysis can be created. However, this methodology could also be combined with other frameworks and methods like Osterwalder et al. (2005) suggest. Especially in case of the analysis of the value network additional frameworks and tools might be needed to get the required input for the checklist anyway. Additionally, the proposed method should be developed further to expand the potential number of users.

Potential Disruptive Technologies in Telecommunications Analyzed Ex Ante As already mentioned above, there have been a few historic examples of successful disruptions in the telecommunications industry, especially in the equipment area, such as Cisco’s development of the router or ROLM’s creation of the PBX (Private Branch eXchange) market (Christensen et al., 2004). However, none of these innovations led to a widespread change in the telecommunications services. Therefore, much emphasis in recent research has been placed on the perspective of incumbent service providers (fixed and mobile) like Verizon, AT&T, Deutsche Telekom, BT, Vodafone, China Mobile, NTT, etc. who could be in danger of being disrupted by new entrants with technologies like VoIP, WLAN (Wireless Local Area Network or IEEE 802.11), or cable telephony, etc. (Christensen et al., 2004; Hüsig et al., 2005; Mannings & Cosier, 2001; Osterwalder et al., 2005; Rao et al., 2006). Historically speaking, the incumbents in telecommunications were highly vertically integrated, owned large established networks, and enjoyed high grossmargins while providing a high quality, mainly voice-based service (Christensen et al., 2004). Therefore, recent changes coming from the data and Internet industry as well as disintegration tendencies have been drawing the attention of industry, policy makers and researchers as a prime source of potential disruptions for the telecommunications service providers. The paradigm shift from centralized-wired-voice to decentralizedwireless-data could render traditional incumbents increasingly irrelevant. On the other hand, highly interdependent networked industries like telecommunications with significant network effects, in which regulation, and scarce resources play an important role, typically provide better avenues for co-option in favor of the incumbent telecommunications firms. Therefore, a more specific

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analysis for each potential disruptive technology is required. In this section a few published examples of potential disruptive technologies in telecommunications which were analyzed ex ante are presented, and a deeper look at the WLAN technology is taken.

Examples of Potential Disruptive Technologies in Telecommunications There are already some examples of potential disruptive technologies in the telecommunications industry which have been analyzed ex ante in the academic literature. Some of these examples are given in Table 1. All of these examples are analyzed from the perspective of the incumbent service providers. In the cases of cable telephony, VoIP and wireless voice, the most threatening incumbents are the fixed line incumbent service providers. Wireless data/WLAN is typically seen as a threat to mobile service operators (MNOs). The results of the various authors were summarized when the studies were published and compared to the status quo in 2008. So far the track record of the ex ante studies looks quite good from today’s perspective, although – even though a couple of years have passed – some of the developments are still unclear, such as the effects of instant messaging or VoIP on the telecommunications incumbents. This underlines the

long-term process characteristics of the disruption phenomenon. However, most studies do not pay much attention to the geographic dimension and assume that the disruptive potential is similar everywhere, or concentrate implicitly on the USA market. This might underestimate different institutional conditions which influence the disruption potential (Chesbrough, 1999, 2003; Hüsig et al., 2007). In the next section the case of the WLAN technology is discussed to illustrate an example of a potential disruptive technology in telecommunications which was analyzed ex ante in greater depth.

The Disruptive Potential of WLAN for the MNOs Various authors from business and academia have suggested that there is a disruptive potential of WLAN technologies for MNOs (Hüsig et al. 2005; Christensen et al. 2004). In particular, WLAN could be disruptive for incumbent MNOs’ third generation (3G) data services, since they enable wireless Internet service providers (WISPs) to offer short distance, high bandwidth data services in heavily trafficked areas known as “hotspots”. This new entrant WISPs could partly bypass the MNOs’ data services based on licensed band mobile communication standards like GSM, GPRS or UMTS. These studies have frequently taken an ex ante perspective, since the public hotspot

Table 1. Examples of academic studies of potential disruptive technologies in telecommunications

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Analyzed technology/Innovation

Analyzed disruptive potential

Analysis by

disruptive potential to date (2008)

W ireless V oice

H igh b ut c o-opted by incum bents

C hristensen et a l. ( 2004)

H igh b ut c o-opted by incum bents

V oice over Internet P rotocol ( V oIP )

H igh b ut c o-opted by incum bents

C hristensen et a l. ( 2004) O sterw alder et a l. ( 2005) R ao et a l. ( 2006)

U nclear

C able T elephony

Low , m ore s ustaining

C hristensen e t al. ( 2004)

Low , m ore sustaining

W ireless D ata/W LA N

A verage, co-option by incum bents m ost lik ely

C hristensen et a l. ( 2004) H üsig et a l. ( 2005)

C o-opted and d om inated by incum bents in m ost m ark ets

Instant M essaging

H igh

C hristensen et a l. ( 2004)

U nclear

Analyzing the Disruptive Potential in the Telecommunications Industry

market has been developing rapidly. The study by Hüsig et al. (2005) used the method elaborated in this chapter. The authors came to the conclusion that WLAN was not very likely to represent a disruptive technology for the incumbent MNOs. This conclusion was drawn by a rigors analyses process which included the following steps: 1.

2.

3.

4.

5.

6.

Information and data gathering process using the checklist as guideline for interviews of interdisciplinary experts and to gather additional required data from market reports and various studies. The value network and the metrics of value in mobile communications at the time of analysis were specified. The basic characteristics of the WLAN technology and the mobile communication standards and their evolution over time were described. The performance demand characteristics for wireless data services and applications and their evolution over time were qualified and quantified. A trajectory map with both technologies together with the performance demand characteristics in the time-span of 1997-2005 was developed. The checklist was used to analyze the gathered data and develop the final result for the disruptive potential.

The result of this process is summed up here briefly. The analysis of the disruptive potential using the methodology described above provided an overall disruptive potential score of 10 disruptive vs. 21 non-disruptive criteria and 7 unknown criteria. The key rationale for this conclusion is presented as follows. The conclusion that the likelihood of WLAN disruption for the MNOs was low was mainly due to the superior performance attributes in bandwidth, one of the most valued attributes for data services and the targeted customer group – business customers, who rep-

resent the most profitable segment in the value network of the threatened MNOs. The viewpoint was taken by Hüsig et al. (2005) that the existing WLAN based services at that point of time were not aimed particularly at downmarket segments with modest performance requirements but at the upmarket segments of business customers with high performance requirements, which does not indicate a typically disruptive pattern. From this viewpoint, WLAN enabled the existing consumers on the mainstream market to do things they could do previously, but not as well and probably less conveniently given the limitations of existing MNO services like WAP with low data rates when they wanted to connect to the Internet outside the office. Therefore, there were only underserved but no overserved customers in the mainstream market of MNOs, providing a potential for a radical sustaining upmarket innovation (Hüsig et al., 2005). Since almost everyone is an MNO customer, potential hotspot users and MNO customers have a high overlap, which leads to the conclusion that WLAN technology did not create a new customer group. Moreover, as accessing mobile data with high speeds has been valued by the high end customers, but not sufficiently enabled by existing MNO technologies and services, WLAN did not create an entirely new or low-end application for mobile data communication. Following this line of argument and taking the theory of disruption into account, Hüsig et al. (2005) concluded that in the case of WLAN no different levels of customer pressure and therefore no asymmetrical motivation between incumbent and entrant should exist, which favors a sustaining scenario for the WLAN technology. It was predicted that the appeal of WLAN for the incumbent MNOs’ most valuable customers would force the MNOs to invest in this radical sustaining technology rather than to ignore it. Furthermore, without asymmetrical motivation, entrants’ prospects seem to be rather limited in the long run given the wealth of the MNOs’ resources which could be brought into the competitive arena. So far only limited empirical

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evidence from the hotspot market is available, but in most countries primarily the incumbent MNOs have taken advantage of the opportunity provided by the WLAN technologies and the hotspot market (Hüsig et al., 2007). This would support the results from the ex ante analysis performed with the methodology presented above.

Future Trends and Conclusion In this article a method for assessing technologies for their disruptive potential from an ex ante perspective in the telecommunication industry was presented based on research by Hüsig et al. (2005) using the fundamentals of the disruptive technology concept pioneered by Christensen (1997), and recent theoretical developments. Even with the support of this methodology, it remains difficult to analyze the telecommunications sector using this theoretical underpinning as network effects, regulation, and scarce resources (e.g. frequencies) often play an important role in the adoption and diffusion of new services and technologies (Hüsig et al., 2005; Mannings & Cosier, 2001; Schoder, 2000). However, recent research in the telecommunications sector using the disruptive innovation framework shows the feasibility of the methodology in this industry (Christensen et al., 2004; Hüsig et al., 2007; Hüsig et al., 2005; Osterwalder et al., 2005; Rao et al., 2006). Major differences seem to be rooted in the fact that the incumbents in highly interdependent networked industries provide better avenues for co-option in favor of the incumbent telecommunications firms (Christensen et al., 2004). Moreover, this method should be seen as part of a broader analytical process, in which it supports the first disruptive technology scanning phase. The degree of disruptive potential can be measured by the relative number of disruptive characteristics fulfilled. The result gives an indication of how threatening the

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potentially disruptive technology is likely to be at a certain point in time, especially if a large group of interdisciplinary experts can be surveyed in order to provide an aggregated analysis (Hüsig et al., 2005). Finally, this method is especially useful as a guide for users who are already familiar with Christensen’s theory and who wish to conduct interviews with experts from different domains to gather and analyze the necessary facts in a structured way. The value added of this method is to help managers, policy-makers and analysts systematically forecast the progress of disruptive technologies. An interdisciplinary group of experts is suggested to ensure that both the market and technological aspects are covered. In the case of telecommunications also the institutional and legal aspects might require special attention, so that also this type of experts must be considered. There are some limitations that may hinder the reliability of this methodology, such as the quality of the input information provided, or the different emphasis with which certain aspects of the disruptive attributes are taken into account. The choice of performance criteria can also influence the result, as in most value networks the highest rank-ordering criteria are difficult to identify and technological trade-offs between performance criteria exist. However, as the studies on disruptive potential in telecommunications presented here indicate, most of the limitations can be successfully managed and useful ex ante analysis results can be provided. Future research in this area should develop these methods further and improve the theoretical underpinning of the disruptive technology concept. From an empirical viewpoint, existing studies on potential disruptions in telecommunications need to be updated and monitored to evaluate how effectively they help managers, policy-makers and analysts systematically forecast the progress of disruptive technologies.

Analyzing the Disruptive Potential in the Telecommunications Industry

Table 2. Checklist with the main indicators for analyzing the disruptive potential modified from Hüsig et al. (2005) disruptive potential checklist

yes

no

unknown

Is there a technology w ith disruption potential? D oes your firm have a potentially threatened technology (P T T )? Is the P D T (potentially disruptive technology) based on an architectural innovation? Is the P D T technologically straightforw ard, consisting of standard com ponents? D oes the P D T underperform w ith regard to m ost-valued perform ance dim ensions? A re products based on a P D T already applied outside the m ainstream m arket and your firm ? H ave prototypes or products based on the P D T been developed in your firm ? Is the P D T aim ed m ore at unpredictable than predictable needs of existing custom ers? A re the P D T initial cost/benefit characteristics not com petitive w ith existing custom ers? H ave existing custom ers show n a negative response to products based on the P D T ? A re the products based on the P D T only useful for m ainstream custom ers in a lim ited w ay? A re the custom er needs or requirem ents regarding the P D T largely ill-defined or unknow n? D oes the P D T also attract less skilled consum ers? D oes the P D T also attract less w ealthy consum ers? D o the incum bents doubt w hether there actually is a m arket for the P D T ? A re sm aller m argins expected for the products based on the P D T ? A re the products based on the P D T sim pler, cheaper, m ore reliable or m ore convenient? D o the products based on the P D T have a w orse cost- or price-perform ance ratio? A re the perform ance attributes of the products based on the P D T a disadvantage? H ave the projects for putting the P D T on the m arket been stopped? A re there new firm s that offer products based on the P D T ? H ave these new firm s successfully created new m arkets for the P D T ? C an these new firm s achieve an attractive rate of return w ith products based on the P D T ? D o the perform ance attributes based on the P D T develop faster than the new dem and? D o the perform ance attributes based on the P D T develop faster than the old dem and? A re the first products based on the P D T aim ed prim arily at dow n-m arket segm ents? D o the established firm s reject introducing products based on the P D T ? H as your firm reacted by introducing products based on the P D T onto the existing m arket? A re these products based on the P D T prim arily aim ed at custom ers in the existing m arket? A re your products based on the P D T m arketed separately from an independent organisation? A re there no principal reasons that could im pede the im plem entation of the P D T ? A re there changes in the m ost-valued perform ance attributes on the m ainstream m arket? Is there less w illingness to pay for an increase in m ainstream perform ance attributes? A re there custom er groups w ith different dem ands regarding perform ance attributes? D oes the P T T overshoot the perform ance requirem ents of the less-dem anding custom ers? D oes the P D T overshoot the perform ance requirem ents of the less-dem anding custom ers? D oes the P D T ’s trajectory of perform ance supply intersect w ith the trajectory of perform ance dem and at the low end of the established m arket? D oes the P T T undershoot the perform ance requirem ents of the new custom ers? overall disruptive potential score

References Adner, R. (2002). When are Technologies Disruptive? A Demand-Based View of the Emergence of Competition. Strategic Management Journal, 23, 667-688. Adner, R., & Levinthal, D. (2001). Demand Heterogeneity and Technology Evolution:Implications for Product and Process Innovation. Management Science, 47(5), 611 –628. Bores, C., Saurina, C., & Torres, R. (2003). Technological convergence: A strategic perspective. Technovation, 23(1), 1-13.

Bower, J. (1970). Managing the Resource Allocation Process. Homewood, IL.: Irwin. Burgelman, R. (1983a). A model of interaction of strategic behavior, corporate context, and the concept of strategy. Academy of Management Review, 3(1), 61-69. Burgelman, R. (1983b). A process model of internal corporate venturing in the diversified major firm. Administrative Science Quarterly(28), 223-244. Chandler, G. (1999). How to set up a forecasting system in telecommunications industry. The 121

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Journal of Business Forecasting Methods & Systems, 18(2), 3-6. Chesbrough, H. W. (1999). The organizational impact of technological change: a comparative theory of national institutional factors. Industrial and Corporate Change, 8, 447-485. Chesbrough, H. W. (2003). Environmental influences upon firm entry into new sub-markets: Evidence from the worldwide hard disk drive industry conditionally. Research Policy, 32(4), 659-678.

Danneels, E. (2004). Disruptive technology Reconsidered: A Critique and Research Agenda. Journal of Product Innovation Management, 21(4), 246-258. Gilbert, C. G. (2002). Beyond Resource Allocation: Towards a Process Model of Response to Disruptive Change. Harvard Working Paper #03-018. Gilbert, C. G. (2005). Unbundling the Structure of Inertia: Resource versus Routine Rigidity. Academy of Management Journal, 48(5), 24.

Christensen, C. M. (1992). Exploring the Limits of the Technology S-Curve. Production and Operations Management, 1(4), 334-366.

Gilbert, C. G., & Bower, J. (2002). Disruptive Change - When Trying Harder Is Part of the Problem. Harvard Business Review, (5), 94-101.

Christensen, C. M. (1993). The Rigid Disk Drive Industry: A History of Commercial and Technological Turbulence. Business History Review, 67(4), 531-588.

Govindarajan, V., & Kopalle, P. K. (2006a). Disruptiveness of innovations: measurement and an assessment of reliability and validity. Strategic Management Journal, 27, 11.

Christensen, C. M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Boston/Massachusetts: Harvard Business School Press.

Govindarajan, V., & Kopalle, P. K. (2006b). The Usefulness of Measuring Disruptiveness of Innovations Ex Post in Making Ex Ante Predictions. Journal of Product Innovation Management, 23, 7.

Christensen, C. M., Anthony, S. D., & Roth, E. A. (2004). Seeing What’s Next - Using the Theories of Innovation to Predict Industry Change. Boston: HBS Press. Christensen, C. M., & Bower, J. (1996). Customer Power, Strategic Investment, and the Failure of Leading Firms. Strategic Management Journal, 17, 197-218. Christensen, C. M., & Raynor, M. E. (2003). The Innovator’s Solution: Creating and sustaining successful growth. Boston, Massachusetts: HBS Press. Christensen, C. M., & Rosenbloom, R. S. (1995). Explaining the Attacker’s Advantage: The Technological Paradigms, Organizational Dynamics, and the Value Network. Research Policy, 24, 233-257.

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Hüsig, S., Dowling, M., & Hipp, C. (2007, 1-3 June). Analysing the Disruptive Potential of WLAN: A Three-Country Comparison of the Hotspot Market. Paper presented at the 5th International Symposium on Management of Technology, Hangzhou, P.R. China. Hüsig, S., Hipp, C., & Dowling, M. (2005). Analysing Disruptive Potential: The Case of W-LAN and the Mobile Telecommunications Network Companies. R&D Management, 35(1), 17-35. Lia, F., & Whalleyb, J. (2002). Deconstruction of the telecommunications industry: from value chains to value networks. Telecommunications Policy, 26(2), 451–472. Lyytinen, K., & King, J. L. (2002). Around the cradle of the wireless revolution: the emergence

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and evolution of cellular telephony. Telecommunications Policy, 26(3-4), 97-100.

tentially disruptive technology is likely to be at a certain point in time.

Mannings, R., & Cosier, G. (2001). Wireless everything — unwiring the world. BT Technol J Vol 19 No 4 October 2001, 19(4), 65-76.

Disruptive Technologies/Innovations: Technologies or innovations which disrupt an established trajectory of performance improvement downwards, or redefine what performance means. In the long run the initially inferior technologies from new markets or low end market segments typically introduced by new entrants become good enough to meet the demands of the mainstream customers of the incumbents, so that the incumbents are forced toward higher margin customer groups or out of the market entirely.

Osterwalder, A., Ondrus, J., & Pigneur, Y. (2005). Skype’s Disruptive Potential in the Telecom Market: A Systematic Comparison of Business Models. Retrieved 07.04., 2008, from http://www. hec.unil.ch/yp/Pub/05-skype.pdf Overdorf, M., & Christensen, C. M. (2000). Meeting the Challenge of Disruptive Technology. Harvard Business Review, 67-76. Pfeffer, J., & Salancik. (1978). The External Control of Organisations: A Resource Dependance Perspective. New York: Harper & Row. Rafii, F., & Kampas, P. J. (2002). How to identify your enemies before they destroy you. Harvard Business Review, 80(11), 115–123. Rao, B., Angelov, B., & Nov, O. (2006). Fusion of Disruptive Technologies: Lessons from the Skype Case. European Management Journal, 24(2-3), 174-188. Schoder, D. (2000). Forecasting the success of telecommunication services in the presence of network effects. Information Economics and Policy, 12(2), 181-200.

Key Terms Disruptive Potential: Concept and measure for ex ante analysis of the potential of emerging technologies to reach the end of the disruption process successfully. The degree of disruptive potential is measured by the relative number of disruptive characteristics fulfilled. The result gives an indication of how threatening the po-

Entrants: New firms in a certain value network. Often entrants introduce potentially disruptive technologies in traditional value networks. Examples in telecommunications are Skype or Cisco. Incumbents: Traditional and typically large firms which operate in an existing value network. Frequently their successfully manage sustaining innovations. Examples in telecommunications are BT, Vodafone, NTT, France Telecom or Deutsche Telekom. Innovation: Changes in the technology of an organization. Sustaining Technologies/Innovations: Technologies or innovations which have a sustaining impact on an established trajectory of performance improvement and give the known customers more and better versions of what they have valued up to now. They lead to innovations that allow the firms to provide their existing customers with better and more profitable products. Incumbent firms almost always ultimately master this type of innovation but are often unable to cope with disruptive ones. Technology: The process by which an organization transforms labor, capital, materials, and information into products and services.

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Value Network: The context within which a firm identifies and responds to customer needs, solves problems, procures input, reacts to competitors, and strives for profit.

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Chapter VIII

Convergence of the Internet and Telecommunications John B. Meisel Southern Illinois University Edwardsville, USA Timothy S. Sullivan Southern Illinois University Edwardsville, USA

Abstract The local exchange telephone market is no longer considered to be a natural monopoly as a result of technological advancements. In particular, the power, versatility, and adaptability of digital technology has enabled traditional telecommunications companies to transition their network architecture from one based on copper wires and circuit switches dedicated to the provision of high quality transmission of point-to-point voice signals to a multi-faceted, general network based on fiber optic cables and packet switches capable of providing an array of voice, data, and video services. A network layers model is introduced to conceptualize the process of convergence to the Internet model. Convergence is fundamentally changing the nature of what it means to be a telecommunications company and promises to alter the market structure of many voice, data, and video markets. Convergence has pitted wireline telecommunications companies in a fierce rivalry with cable companies for voice, data, and, increasingly, video services. More generally, this research provides a framework to explain the convergence of communications networks and identifies and analyzes key issues that confront public policymakers. One key competition issue, termed network neutrality, addresses the concern that the evolving broadband network architecture will enable network providers to favor the provider’s services or affiliated services at the expense of independent rivals. Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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INTRODUCTION At the close of the 20th century, a traditional, prototypical telecommunications company provided high quality point-to-point voice services utilizing a technology specially designed for transmitting voice signals. This wireline architecture was comprised predominantly of copper-based local loops, circuit switches, and local transport and long distance conduits that incorporated some fiber-optic technology. In such centralized phone networks, intelligence resided in the core of the network in the switch technology, not in the end devices connected to the network as it does in the decentralized Internet architecture. In such a network, the provision of the service, voice, was closely identified with the underlying physical infrastructure that provided the service. For much of the 20th century, United States telecommunications companies were thought to be natural monopolies in the provision of voice services and thus subject to regulation in dual jurisdictions, at the state and federal levels. More generally, regulation of electronic communications networks was based on the premise that a particular service (such as voice, data, or video) was inextricably linked to a specific underlying infrastructure used to provide the service. With technological improvements in digital and network technology and the spectacular growth of broadband technology and the Internet at the end of the 20th century, the traditional architecture of phone networks (and other communications networks) and the scope of regulation of telecommunications companies are gradually changing. Telephone companies are transforming their provision of voice and other broadband services from copper-based networks to advanced fiber-optic networks. The purpose and scope of this research is to describe and analyze the restructuring of telecommunications networks and telecommunications companies as they respond and adapt to technological and economic changes.

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As telecommunications/entertainment/information networks converge to an advanced, multifaceted architectural broadband platform that is capable of offering an integrated bundle of voice, data, and video broadband services, it is incumbent on regulatory authorities to change the nature of the regulatory approach toward these telecommunications companies. A pattern of deregulation is in process but there still exist unanswered questions regarding the appropriate regulatory response to convergence. Convergence is creating new competition/regulatory issues in a variety of formerly distinct industries. Peha, Lehr, and Wilkie (2007), three leading Internet scholars, argue that “At root, the debate is about the future of regulatory policy for the communications sector as we move toward a post-convergence world where legacy industry boundaries and regulation of cable television, broadcasting, and telecommunications need to be reconciled with the challenges of competition among broadband platform services, based on the Internet” (p. 710). For instance, as the telecommunications network converges on the Internet model, telephone companies have discussed implementation of a twotiered (non-neutral) Internet that would replace the standard practice by Internet service providers of treating generally all kinds of packets in the same manner (i.e., neutrally) regardless of the application or provider. Observing a neutrality principle implies that broadband access providers do not favor some packets at the expense of others, that is, there exists a lack of discriminatory behavior toward applications and content utilizing the network. A two-tiered Internet can be viewed as a strategic maneuver by vertically integrated broadband service providers to gain a competitive advantage in the market for Internet services and applications. Richard Notebaert, Chief Executive Officer of Qwest Communications, for example, argues that telephone companies should be able to negotiate commercial agreements with content

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providers such as Google or Amazon to give Internet companies an advantage over rival firms because, “we’re all trying to provide a little bit of differentiation for a competitive edge. That’s what business is about” (Reardon, 2006a). With a non-neutral Internet, broadband access providers install intelligence within the network in order to favor some packets and disfavor others and, hence, exert control over applications and content utilizing their network. The controversy over implementation of a non-neutral platform is captured in the term net neutrality. Potential competitive issues arising from the design and implementation of a two-tiered broadband architecture involve (1) a telecommunications company’s treatment of an emerging Internet service (such as Voice over Internet Protocol (VoIP)) that competes directly with the company’s core, legacy service, (2) a telecommunications company’s treatment of its newly created or purchased/favored affiliated Internet content and/or Internet application service that competes with a non-affiliated company’s substitute service, and (3), more generally, the ability and incentive of a telecommunications company to attempt to leverage market power in broadband access into Internet services dependent on a broadband platform. Issues involving the concept of net neutrality are examined using an antitrust framework. Such a policy framework is appropriate since technological and economic changes and the convergence of previously distinct network architectures (such as the telephone and cable networks) to the advanced broadband Internet model is increasing the number of competitors facing telephone companies. The era of telecommunications natural monopoly is over and the advent of inter-platform competition is here. The next section explains the term convergence and compares and contrasts the current telephone network with the broadband Internet network and describes the evolution of the telephone network to the advanced Internet broadband architecture using the concept of the network

layers model. The following section describes the changing nature of the external environment confronting telephone companies and explains how these companies are adjusting to technological convergence, regulatory changes, and economic competition. The remaining sections identify and analyze competition issues involving broadband service providers that result from the convergence to the Internet broadband architecture and provide a summary.

CONVERGENCE For most of their existence, telecommunications companies were viewed as specialized providers of voice services using a unique copper-based technology. That is, a telephone company’s network architecture was dedicated to provide analog voice services and the physical components of the network included circuit switches, copper local loops, and high capacity transport and long distances lines. The transition to a new broadband architecture based on the Internet protocol is underway. The transitional network architecture is characterized by local loops, part copper and part fiber, carrying a combination of digital and analog signals. Signals today reach their final destination by traveling through either circuit switches and/or packet switches in local and long distance transmission links increasingly built with fiber. This transitional architecture enables telecommunications companies to provide a combination of voice and data, especially narrowband and broadband Internet access, services. The current architecture is likely to evolve to an all fiber-based, digital packet-switched broadband network capable of transmitting voice, data, and video services. The transition and transformation of telecommunications networks can be described and analyzed using a network layers conceptual model. (See, for example, Nuechterlein & Weiser, 2005, Chapter 4; Whitt, 2004 and Werbach, 2002.)

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Network Layers Model The network layers model is an analytical tool that views a communications network as a set of discrete, functional layers. That is, the concept of a layered network means unbundling the complex task of provisioning a communications signal into smaller, discrete subunits, each of which is designed to address a specific task. Each layer in the network contributes to the provision of a communications service within a hierarchical framework. Each layer has interfaces that facilitate its coordination with adjacent layers. Each distinct layer of a communications network can be examined to assess the lack of or degree of horizontal competition from competing networks within a given layer (e.g., competing instant messaging applications, competing email applications, competing infrastructure providers) as well as its vertical relationship to adjacent layers. Table 1 provides an overall schematic of the model. The lowest layer (layer 1) is called the physical access layer. (See, for example, Whitt, 2004, and Weiser, 2003.) This layer is associated with the physical infrastructure and includes elements such as personal computers, servers, smart devices,

copper-based local loops, fiber-based local loops, circuit and packet switches/routers, digital subscriber lines (DSL), cable modems, coaxial cable, power lines, radio towers and antennas, and long distance trunks. This layer is responsible for the transmission of content between users within a network or across networks. Service providers at this layer provide two basic services: (1) local shared transport (transmissions from end office switches to tandem switches) and long haul backbone services which involve high capacity lines connecting tandem switches and network access points that interconnect different networks, and (2) local access services which involve the provision of first-mile and last-mile dedicated (or shared among a small number of customers) connections between end offices and local residences and businesses. Service providers at layer 1 include telephone companies, cable companies, and wireless companies. On top of the physical access layer sits the logical layer (layer 2). This layer in essence identifies the common language that enables different computers around the world to communicate. In other words, this layer manages how information travels over the Internet. It involves a set of

Table 1 Schematic of the network layers model Layers

Typical Providers

Content Layer

Entertainment companies, information companies such as NBC, ABC, CBS, ESPN,CNN, FOX

Video, text, audio, voice Applications Layer Email, peer-to-peer, instant messaging, electronic commerce, search, voice over Internet protocol, video hosting, video conferencing Logical Layer Open set of protocols, such as TCP/IP protocol suite Physical Layer Loops, switches, trunks, routers, cellular towers

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Developers of software such as Google, eBay, Skype, Yahoo, YouTube, Vuze, BitTorrent, Microsoft

Broadband service providers, includes telephone and cable companies

Network providers such as Comcast, AT&T, Verizon, Qwest, Time Warner, Madison River Communications

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intelligent protocols that lays out the ground rules for communication. Information is assembled into packets with a specific format that includes addressing rules, the Internet Protocol (IP), and rules to inform packet switches along the way, the transmission control protocol (TCP), where the packets want to go. In short, the Internet protocol packages and routes data. These protocols work on top of any configuration of the physical layer. Importantly, these protocols have become network software standards and lay in the public domain for use by any applications developers. Internet access providers provide access to the Internet and operate at layer 2. The third layer in the model is the applications layer. Applications such as e-mail, the World Wide Web, search engines, instant messaging, and audio and video players have spurred the growth of the Internet. These applications reside as software on computers and servers. Applications are based on layer-two logical software for addressing and transmission and add their own innovative protocols for computers to exchange information. The creation of new applications provides incentives for users to use the Internet and to upgrade their broadband access to enjoy more bandwidth intensive and real-time applications like peer-to-peer file sharing and real-time video. Given the layered and modular nature of the Internet, applications developers need only concern themselves with writing code for new applications compatible with the IP protocol and not be concerned with also provisioning physical infrastructure and/or logical protocols. (Contrast this, for instance, with an inflexible centralized architecture such as the original telephone network, where, if a developer wished to provide a new application for the network, the application developer must seek permission from the network’s owner to do so and must configure the application to the specific network’s underlying physical infrastructure and logical code.) Application service providers include independent Internet companies such as Google, Amazon, and eBay as well as layer-1 and -2 vertically integrated service providers.

The fourth layer of the model is content. This is the actual information that is exchanged. Movies, music, voice communications, and data can all be digitized and exchanged between computers using the three lower layers. Content is what users are ultimately interested in exchanging with others. Commercial entertainment, information, communications companies, and increasingly today, amateur end users create content and thus operate at layer 4. The wireline telephone network has been upgraded to provide voice and broadband services using a digital subscriber line (DSL) architecture. This means that telephone companies are simultaneously operating two networks, a dedicated circuit-switched voice network and more general packet-switched data network. This enables telephone companies to utilize their preexisting copper local loops to residences and businesses and to upgrade the services provided to these customers. Thus, a telephone company integrates layer 1 and 2 functionalities for it provides basic transmission and enhanced computer processing of data for the customer. A residential customer can use the local loop to both make voice calls that travel over the circuit-switched public telephone network and to access the Internet over a broadband connection using the packet-switched Internet to reach the intended destination. The likely goal of telephone companies is to continue the evolution of their networks to the Internet model in which they provide all services over the Internet platform, ultimately, including voice services.

Economic, Regulatory, and Technological Environments Telephone companies are not alone in adapting to the inexorable trend toward technological convergence as their current network architecture transitions to incorporate the Internet layers model in order to offer additional services built on the underlying physical infrastructure. Operators of cable television systems are undergoing a similar

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transition. (It should be noted that operators of power lines, satellite systems, and private and municipal wireless systems are also creating or upgrading networks to provide enhanced broadband Internet access and upper layer services.) As well as providing multichannel video programming, cable companies today provide their customers broadband Internet access and voice communications, often using VoIP technology. That is, voice becomes an Internet application that rides on top of the logical and physical layers of a cable network. Cable companies are now in direct competition with telephone companies as “triple play” providers of broadband Internet access, voice communications, and multichannel video distribution. As of the end of 2006, there were five million subscribers in North America that purchased three communications services from the same company (which at this point is overwhelmingly a cable company). The predicted number increases to 10 million by 2010 (Britton & McGonegal, 2007). These competitors utilize different physical infrastructures but as they transition to the Internet layers model they are in a position to provide similar services that are built on the same logical IP protocol. This transformation of telephone and cable networks has forever severed the link between a specialized service and a specific underlying physical architecture. As noted above, cable television and phone services are undergoing a remarkable convergence, which is likely to accelerate in response to technological changes. Recently, cable companies have made sizable inroads into the market for telephony service. At first, cable companies constructed physical facilities similar to the telephone companies’ circuit-switched architecture but with technological improvements in broadband networks they have since found it more economical to provide voice services as an application utilizing the broadband networks they were constructing to compete in the provision of Internet broadband services. As of late

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2007, cable companies provided telephone service over their broadband lines to over 12 million US households, or about 11% of the households that are capable of using cable voice service. Comcast, Cox, Time Warner and Cablevision all have more than one million voice subscribers, and virtually all major cable companies offer telephony services (Brumfield, 2007b). While the growth rate has slowed recently, all of these companies continue to add subscribers (Barris, 2007 and Brumfield, 2007a). When stand-alone services, such as Vonage and Skype, are included, over 16 million US households use the Internet for phone service, a number that has nearly quadrupled in less than two years (Mangalindan & Rhoads, 2007). While the stand-alone services have suffered both revenue and legal problems in recent years, cable companies have been fairly successful bundling phone service with other services, such as television and broadband (Shwiff, 2007). While most telephone companies are unable to deliver standard broadcast signals over conventional phone lines, many are partnering with satellite television companies in anticipation of offering television service directly. Verizon, for example, has partnered with DirectTV to offer satellite television service to its residential customers. Similarly, AT&T has partnered with DISH Network, and the two are rumored to be discussing a buyout deal (Moritz, 2007). These partnerships are credited in part with recent declines in the number of video customers held by cable companies (Searcey, 2007). We already are witnessing a rapid expansion of video content provided over the Internet. Currently all of the major US television networks and a sizable number of “cable” networks offer some portion of their primetime schedules online for free. Other programs are offered, for example, through Apple’s iTunes for a fee. Other types of content, traditionally viewed on television, are being introduced at a rapid rate. The National Football League (NFL), for example, offers the SuperFan package, which allows DirectTV cus-

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tomers who purchase the Sunday Ticket package to watch NFL games live over the Internet. Major League Baseball’s MLB.tv allows subscribers to watch live baseball games over the Internet. While relatively inexpensive hardware is already available that allows images on a home computer to be played on a standard television set (and visa versa), advances in LCD technology are likely to increasingly blur the line between television monitor and computer monitor. Advances in broadband access and technology will mean that phone service and television service can both be provided by the Internet, allowing broadband service providers to replace both services regardless of its history as a cable or telecommunications company. Because of the sizable bandwidth requirements for video, adoption of the Internet as a household’s video provider requires a broadband connection. As of late 2007, only 58 million US households are broadband subscribers, accounting for roughly 53% of US households (Malik, 2007). Further, many households currently opt for the slower (and less expensive) downstream speeds of less than 5.0 megabits per second (Mbps). However, as broadband access increases, especially access using far-faster fiber-optic cable, as opposed to standard phone lines and coaxial cable, it is easy to envision the Internet replacing traditional cable and satellite as the primary means of delivering video to US households. At this point, in addition to traditional Internet content, the household’s broadband service provider will become the delivery mechanism for voice and video. The race is on between these two converging industries to be the superior provider of broadband access service (and applications and content) and the early results are as follows: •

The top providers of broadband service are remarkably split between telecommunications and cable companies: o Cable, in total, has a slight overall edge (Grant, 2006).

o

•

•

The top providers are AT&T, with almost 14 million; Comcast, with almost 13 million; Verizon, with almost 8 million, and Time Warner, with over 7 million (Malik, 2007). In the short run, it may be more difficult for phone companies to enter the television market than for cable companies to enter the telephone market because phone companies must expand their networks for greater capacity, while cable companies can use their current infrastructure for some time. Experts are divided, however, whether the cable infrastructure will be able to support greater bandwidth without major investments in infrastructure. Verizon now offers fiber-optic service (FIOS) to Internet customers in 16 states. This fiber-optic network service is capable, in some states, of speeds of up to 50 megabits per second (Mbps). Other phone companies are pursuing a similar strategy, but are focusing on new housing developments (Grant, 2006).

As well as a trend toward technological convergence, telephone companies are active participants in creating a trend toward consolidation of telephone assets and a continuing pattern of telephone deregulation. AT&T was divested in 1984 into (1) a free standing long distance company (called AT&T) that would compete in a competitive market against companies such as Sprint and MCI, and (2) seven independent regional Bell operating companies (Pacific Telesis, U.S. West, Southwestern Bell, Ameritech, Bell South, Bell Atlantic, and NYNEX) that were viewed as natural monopolies in the provision of stand-alone local telephone service in their unique geographic areas and thus subject to continuing regulation. The economic theory in 1984 was that the long distance market was capable of competition safeguarding consumers while local telephone service was not, thus regulation

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was still necessary to protect consumer welfare and to prevent local companies from leveraging their local assets into long distance and enhanced services markets. In the next quarter century and with the intervening passage of the Telecommunications Act of 1996, whose goal was, in part, to promote competition in local telephone markets, the industry has been restructured back toward the original AT&T model of a vertically integrated company. Today, there exist three remaining Bell companies, and AT&T and MCI have been merged into those companies. The demise of AT&T and MCI was mainly due to the rapid decline of the stand-alone long distance business model (in part, due to the entry of the Bell companies into long distance markets) and legal rulings that thwarted their attempts to enter local residential markets using unbundled elements of the conventional telephone network at regulated rates as competitive local exchange carriers. However, these two companies brought assets to their buyers that included long standing business relationships with high volume metropolitan corporate customers who demand sophisticated voice and data services. The three remaining Bells, AT&T (the result of a 2005 merger between AT&T and SBC, which was itself a combination of three Bells, Southwestern Bell, Pacific Telesis and Ameritech, and Bell South), Qwest Communications International (which merged with U.S. West in 2000), and Verizon Communications (the result of mergers between Bell Atlantic and NYNEX and later MCI) are the major telecommunications providers of long distance service, local service and broadband Internet access. It is argued that the real, lasting competition to these wireline companies comes from four national network wireless companies (although two of the largest cellular providers are owned by Verizon and AT&T) and Voice over Internet Protocol (VoIP), an Internet entrant into the voice market (Picker, 2005). Decisions by the Department of Justice and the Federal Communications Commission (FCC)

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to allow the mergers by AT&T and Verizon have been accompanied by certain regulatory conditions placed on the companies. Before examining several specific conditions from these consolidations, several of the most significant deregulatory efforts for telephone companies are in order. A major goal of the FCC since passage of the Telecommunications Act of 1996 has been to promote competition in the lowest layer in the network layers model, the physical infrastructure layer. The Act required the incumbent local exchange carriers to open up their local infrastructure in various ways (e.g., unbundle network elements, act as a wholesaler for their retail service) to facilitate the entry of competitive local exchange carriers. Inevitably, disputes between the incumbents and potential entrants over network access have accompanied FCC deregulation efforts. The Bell incumbents led the resistance to these efforts in court, eventually forcing the FCC to back off from its aggressive efforts to promote last-mile intramodal competition in the traditional telephone network. As of 2007, FCC regulatory efforts appear to be focused on providing incentives for incumbents to upgrade their physical networks, especially toward increased use of advanced technology such as fiber, and to encourage the entry of last-mile inter-modal competition in broadband markets. At the same time, the FCC ruled that Internet access providers using cable modem technology and DSL technology to provide Internet access to residential customers should not be subject to common carrier regulation. DSL service had been subject to common carrier rules including the legal obligation for telephone companies to offer access to its physical transmission lines to the Internet to independent Internet service providers and to rate regulation of such access. The FCC could have decided to include cable companies offering Internet access under the same common carrier regulations. Instead, the FCC ruled that cable and telephone Internet access services should be classified as information services, not

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telecommunications services, and thus, free of Title II regulations in the Communications Act. The US Supreme Court, in 2005, in National Cable & Telecommunications Association v. Brand X Internet Services, upheld the FCC’s classification scheme in its Brand X decision regarding cable modem service. Similarly, the Third Circuit upheld the FCC’s decision that DSL service should be classified as an information service. Effectively, this means that telecommunications carriers and cable companies are not subject to common carrier obligations and, thus, can offer Internet access service, which under the network layers model bundles layers 1 and 2 (the physical layer and the logical layer), without the requirement to provide an open interface between these two layers to unaffiliated competitive Internet access providers. (The term “open access” refers to the ability of independent Internet access providers to lease from regulated tariffs the last-mile facilities (i.e., layer 1) of incumbent common carrier companies.) Thus, a pattern has been established that reduces, if not eliminates, access to the physical layer infrastructure as a method of attempting to move the market structure of the physical layer to a more competitive structure. Again, the FCC’s rationale is based on the argument that regulation diminishes the incentive for incumbents and entrants to invest in advanced infrastructure technology and that regulatory efforts to spur intramodal competition by forced sharing of incumbent telephone companies’ last-mile infrastructure is unfair to incumbents and, in the long term, futile in providing real competition. The next step in the deregulation trend has eased regulations in the commercial broadband market. This involves companies that provide high-capacity broadband services to large corporate customers. The process for deregulation has been initiated by the telephone companies through use of a tool called a forbearance petition. This approach was formalized in the Telecommunications Act of 1996 and allows telephone companies to request relief from regulations that

are no longer necessary due to the presence of competition. Verizon and AT&T have received regulatory relief in this market in response to such petitions (Boles, 2007 and Schatz, 2007). At this time, broadband Internet access to residences and small business, and large business are deregulated. One remaining market still subject to regulation and on the agenda for deregulation is the special access service market. Uses of special access lines include connecting large businesses in metropolitan regions directly to long distance carriers’ points of presence and connecting cell towers to local exchange switches. AT&T is subject to regulation of the special access rate for four years as a condition of the AT&T-BellSouth merger. The issue of the extent of competitiveness of the special access market is still unresolved. Conditions on the telecommunications mergers described above have played a role in the current controversy over the concept of network neutrality. The FCC wishes to maintain the “openness” of the Internet without having to write specific rules to control the behavior of broadband Internet service providers. At the end of 2006, about 95% of 82.5 million last-mile, high-speed lines (including 58.2 million residential lines) are owned by telecommunications companies and cable companies (Federal Communications Commission, 2007). Thus, there exists a concern that these companies may attempt to leverage their market power into competitive applications and content markets. In response to this concern, the FCC conditioned approval of the Verizon-MCI and AT&T-SBC mergers on promises from these companies that they would abide by the “openness” goal for a two year period and follow unwritten net neutrality rules. Specifically, the FCC issued a broadband policy statement that called for, among other things, preserving the neutrality of treatment of packets across the Internet by all broadband service providers (Federal Communications Commission, 2005). More significantly, in the approval of the AT&T-BellSouth merger, a similar net neutrality

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condition was agreed to but with a telling loophole (Reardon, 2006b). AT&T (as well as Verizon) has been upgrading its network infrastructure in order to provide Internet Protocol Television (IPTV) to compete directly with cable and satellite for video viewers (Faulhaber, 2007). The loophole says that AT&T will not have to follow net neutrality principles on the IPTV network for it is a private/managed network but only follow them on their existing public broadband network. Again, this reflects a pattern by the FCC of trying to provide incentives for infrastructure companies to upgrade the technology of the network. Critics worry that the division of the Internet into two parts, a private/managed Internet and a public Internet will create competition problems in the future. Potential competition issues arising from a two-tier Internet is discussed in the next section of the chapter.

COMPETITION ISSUES Telecommunications companies will generate revenue in broadband by (1) selling access to the public Internet (basic access service), (2) selling access to the private/managed Internet (premium access service) and (3) selling its own integrated or affiliated applications and content over the managed network. The antitrust concern is that incumbent broadband Internet access providers, to the extent that they possess market power in broadband access markets, will leverage that power in an anticompetitive manner into presumptively competitive applications and content markets under certain conditions. In general, broadband access providers have a natural incentive to facilitate and encourage the efficient use of broadband platforms for complementary services. More complementary applications and content increase the value to consumers of the platform. The incentive by platform providers to encourage new complementary applications and content is called the principle of

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“internalizing complementary efficiencies” (Farrell and Weiser, 2003). In other words, broadband platform providers generally have no incentive to discriminate against unaffiliated providers of upper layer services for such a strategy is not in the broadband providers’ best profit maximizing interest. However, exceptions to the principle exist, some of which may be relevant to telecommunications companies acting as broadband service providers and the plans they have, in a world of convergence, to integrate vertically into applications and content markets. Exceptions raise the potential for the threat of anticompetitive vertical behavior by broadband service providers toward unaffiliated applications and content providers. In order to offer IPTV and other Internet services, telecommunications companies are in the process of making multi-million dollar fiber-based investments over a period of time to upgrade the supply capability of their broadband networks. Importantly, the way in which the next-generation network is designed (i.e., the architecture of the advanced broadband network) is likely to have long-lasting effects on the structure of Internet markets. According to Nuechterlein and Weiser (2005), “…once a monopolist in a network industry chooses a particular architecture -- say, one that facilitates certain applications for a limited set of preferred providers- network effects may cause the market as a whole to become dependent on that architecture, even if it turns out to have in severable anticompetitive characteristics” (p. 173). In short, network architecture acts as a causal factor for market structure. Network design can result from either technical considerations or from business motivations. As with any investment, the specific question becomes how telecommunications companies are going to generate sufficient revenue to pay off the investment. One option is to offer, as an alternative to the best efforts public Internet, a better than best efforts private Internet. The private/managed Internet would have an enhanced capability to meet the needs of Internet services that require a

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higher quality of service than traditional Internet services such as email, web browsing, and small to medium-sized file transfers. This strategy is called vertical differentiation and attempts to provide a qualitative advantage to packet transmissions over the telephone companies’ private Internet compared to the public Internet. Given the current (de)regulatory environment and after the two year moratorium on capitalizing on vertical differentiation as agreed to during negotiations to win approval of the recent mergers, telephone companies will have the commercial freedom and flexibility to charge applications and content providers for access to enhanced private IP delivery. Public statements by senior executives in the largest telephone companies have expressed a strong interest in capitalizing on this freedom. Moreover, technology (such as deep packet inspection) has advanced to the extent that the ability to discriminate exists through installing intelligence within the lower layers in the network to discover and identify the source, type, and destination of packets. This means that the broadband service provider can uncover information about the packets traveling on its physical infrastructure and dictate the quality of transport a packet is to receive based on this information. The public Internet is coping with the increased heterogeneity of demand from new services. Streaming video and peer-to-peer video file transfers are bandwidth intensive services while VoIP and online gaming are sensitive to delay in delivery of packets and to variation in that delay. These new demands have strained the supply capability of the best effort, neutral treatment of all packets, public Internet. (Swanson, 2007, provocatively refers to the predicted tremendous increase in demand for broadband capacity as the coming “exaflood.”). In order to address the needs of these new services, a discussion has ensued about the appropriateness of broadband access providers providing differentiated quality of service to applications and content providers, and end users.

In order to receive a return on their investment in the next-generation broadband network, telecommunications companies want to differentiate vertically the quality of Internet access they provide to applications and content providers to reach end users. Telecommunications companies plan on restricting access to the non-neutral Internet that provides a higher quality of service than the neutral Internet, and, then, offer a higher quality of service as an option for applications and content providers such as Google, Amazon, Vonage, and Yahoo to reach end users. In general, Internet companies are opposed to the idea of having to pay access fees to reach end users and support legislation to mandate the existing neutral Internet for they believe that neutrality is most conducive to enhancing the incentives of applications and content providers to innovate. (See Frischmann and van Schewick, in press, for a compelling argument that fostering innovation in Internet applications and content is the primary motivation behind net neutrality legislation). Proponents of net neutrality desire a regulatory/legislative safeguard against potential discriminatory behavior, as manifested in a two-tier Internet, by broadband service providers toward unaffiliated applications and content providers. Opponents of network neutrality legislation/ regulation see this rationale as self-serving and portray legislation as an attempt to reduce competition among existing Internet companies and to create a barrier to entry to applications and content markets (see Sidak, 2007, for a forceful argument for this position). Moreover, critics point out that independent applications and content providers have market alternatives to broadband service providers to improve the quality of their delivered service. Two examples are to self-provide distributed capacity and to purchase enhanced quality of service from competitive content delivery network providers such as Akamai. One competition issue associated with network neutrality examines the state of horizontal competition between broadband service provid-

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ers. From a customer’s perspective wishing to purchase a broadband connection to the Internet, net neutrality proponents see very little structural competition (most consumers face a duopoly market structure) while net neutrality opponents see strong behavioral competition (declining prices for broadband Internet access and better quality connections) between telephone and cable companies, as discussed above, with potential competitors on the brink of entry into the market. Opponents could cite as an example of potential competition the announcement by Google to purchase spectrum in a forthcoming FCC auction to build purportedly a national mobile carrier network. This network could serve as an open platform to the Internet (Delaney and Sharma, 2007). Regulatory decisions not to require open access to the physical layer owned by wireline broadband access providers implies that structural competition to the incumbents will come from new technologies, such as wireless, and not from intra-platform (intra-modal) wireline competition. (European regulators continue to see the benefit to society from fostering intra-platform competition by proposing to separate the incumbent wireline provider’s network into wholesale and retail divisions, referred to as “functional separation.” For a criticism of this approach, see Crandall, 2007.) Moreover, some critics of net neutrality legislation argue that policy makers should not focus their efforts on promoting competition in the applications and content layers but rather in the physical layer for that is the location of concentrated economic power in the network layers model. (See Yoo, 2005, for an articulate argument for this position.) As the market reaches a mature state, a related issue impacting consumer welfare in the broadband access market concerns the significance of switching costs. Future competition will involve attempts to entice consumers to switch broadband technologies as opposed to convincing consumers to upgrade to a broadband connection. To the extent that economic and technical obstacles

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hamper the ability to switch easily technologies for broadband access, the market power of incumbent access providers is enhanced, even in a market with several rival broadband suppliers. A militating factor to broadband access providers’ ability to exercise economic power over residential customers is the availability of commercial and institutional broadband access for consumers when they are at work or school. Such access would serve as a substitute to broadband access at home (Owen and Rosston, 2003). A two-tier Internet, consisting of a private/ managed Internet and a public Internet, can give rise to an exception to the Chicago-School theory that broadband service providers will only encourage efficient use or discourage inefficient use of its platform. The potential for anticompetitive vertical strategic behavior by incumbent broadband access providers exists to the extent that services of unaffiliated applications and content suppliers are viewed as good substitutes or potential substitutes for Internet services telephone companies actually offer or plan on provisioning. The most obvious example of the incentive for a telephone company to discriminate in an anticompetitive manner is toward an Internet voice competitor such as Vonage. For example, a telephone company could block access to its broadband customers for a close substitute VoIP service. Such straightforward and transparent discrimination is likely to lead to a political and regulatory backlash. (This happened in 2005 when the FCC “fined” a rural telephone company for blocking access to its broadband customers to a VoIP provider’s service.) More likely, telephone companies may confine competitive substitute services to the public Internet in which the quality of service will often be inferior in times of natural or artificially-created congestion to that provided by the telephone company’s service over its circuit-switched telephone network or the private Internet it reserves for its own or affiliated companies’ services. As telephone networks continue to converge to the Internet network’s four layers model,

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telephone companies will increase their ability to provide upper layer services on top of their broadband platform and thus expand the Internet services that they view as good substitutes. (This is similar to the incentive that platform operator Microsoft possesses to expand the features and functionality of its operating system by encompassing services previously offered by independent applications providers.) A good example of this is telephone companies’ provision of IPTV over a private/managed Internet. Consumers are increasingly looking to the public Internet for access to television programming and amateur videos. The accompanying increase in demand for Internet television viewing is bandwidth-intensive and thus taxing the capacity and capability of the best efforts Internet to handle all of the varying demands on its resources. Pioneers of the original Internet argue that the public Internet will soon face a crisis situation as bandwidth intensive applications increase in demand (White, 2007). It is likely that congestion on the public Internet will often lead to inferior video and latency-sensitive experiences for consumers and make the private/ managed Internet video offerings of telephone companies appear relatively more attractive. In a sense, congested public channels will translate into an advantage for integrated and affiliated broadband access providers’ services by acting as a form of raising independent rivals’ costs. Thus, to the extent that access to the scarce channels on the private/managed Internet will grow in demand, this will result in increasing revenues attributably to the private/managed Internet. Broadband service providers possess an incentive to discriminate against substitute services by denying them access to these managed channels while promising that the public Internet will remain open to competitors. Such an incentive could distort competition in Internet markets that require a higher quality of service than the overtaxed public Internet can provide. This could result in Internet service markets (such as the delivery of video programming/content)

becoming concentrated in structure due to the network design and investment decisions by broadband service providers. A perverse incentive exists for broadband service providers since as they increase investment in the public Internet to improve its capacity and performance, the return on their investment in the private/managed Internet decreases. If these events transpire, it is predicted that the next round of the net neutrality debate will involve heated demands for mandated open access to the broadband service providers’ private/managed Internet channels (Faulhaber, 2007, p. 699).

IV. Conclusion Telecommunications companies are well on their way to transitioning circuit-switched dedicated voice networks to packet-switched broadband networks that can support a wide range of IPbased applications and content. Responding to this inexorable path to technological convergence is a federal telecommunications regulatory scheme that has moved from reliance on common carrier regulations to control the market power of telecommunications companies to trust in competition and increased investment in broadband technology to promote consumer welfare. Both convergence and deregulation have positioned telecommunications companies to be strong competitors in this new Internet-based world. It is likely that the carriers will continue to integrate vertically into applications and content markets (layers 3 and 4 in the network layers model) and exploit any competitive advantages associated with a two-tier Internet. Telecommunications companies are familiar with a network in which they control the intelligence, suggesting that they are likely to feel more comfortable with a two-tiered Internet that includes at least one intelligent tier. Limited capacity available in the intelligent private/managed Internet promises to reduce structural competition for some services, such as video programming distribution. 137

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Telecommunications companies will counter criticism of this strategy by pointing to the preservation of neutrality on the increasingly congested public Internet. In this way, incumbent broadband access providers continue to encourage consumer demand due to the wide variety of services they provide open access to, while, at the same time, position their integrated and affiliated services to perform better for the consumer. The tiered position of applications and content is one factor that can contribute to the success or failure of a service. An interesting parallel has been uncovered in the cable television industry. Chen and Waterman (2007), in a recent empirical study, find that “…integrated systems that do carry rival networks often position them on digital tiers having more limited subscriber access” (p. 249). This puts independent cable networks at a competitive disadvantage, notwithstanding the program access rules. Similarly, telecommunications companies will continue to open their networks to rival services but possibly only on the public Internet. It is, thus, likely that a twotiered Internet will (1) dampen the incentive to create new applications and content, knowing that one is confined to an increasingly congested distribution network, and (2) encourage independent applications and content providers to seek intensively for alternative access to consumers. (Superior physical and logical infrastructure can be considered a good substitute for non-neutral quality of service protocols in providing faster, more reliable transmission of data.) One theme of this research is that the architecture of the Internet is a contributing factor in determining the competitiveness of Internet services especially for services that require intense bandwidth or steady transmission speeds. Moreover, once the architecture is in place, changes to that architecture will take significant time and investment. But could it be that the advantages of a twotier Internet are fleeting? If incumbent broadband access providers along with new entrants continue to upgrade the performance of the public Internet,

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the competitive advantage of a two-tier Internet will be eroded over time. Public policy makers’ best bet for such an outcome should focus on fostering new entry by increasing the opportunities to generate revenue and/or reducing the costs of entry into the physical layer.

REFERENCES Barris, M. (2007). Cablevision Posts Wider Loss, Tempers Outlook for New Services. The Wall Street Journal Online Edition, November 8. Boles, C. (2007). AT&T Wins Partial Relief from FCC On Some Broadband Regulations. The Wall Street Journal Online Edition, Retrieved October 12, 2007. Britton, B. B., & McGonegal, S. (2007) The Digital Economy Fact Book, Ninth Edition 2007 (p. 61).Washington, D.C.: The Progress & Freedom Foundation. Brumfield, C. (2007a). Time Warner Cable Falls to 50% Penetration Level. IP Democracy, November 8, 2007, Retrieved May 8, 2008 from http://www. ipdemocracy.com/archives/002755time_warner_ cable_falls_to_50_penetration_level.php. Brumfield, C. (2007b). Is Cable Telephony Growth Tapped Out? IP Democracy, November 15. Retrieved May 8, 2008 from http://www. ipdemocracy.com/archives/002765is_cable_telephony_growth_tapped_out.php. Chen, D., & Waterman, D. (2007). Vertical Ownership, Program Network Carriage, and Tier Positioning in Cable Television: An Empirical Study. Review of Industrial Organization, 30(3), 227-251. Crandall, R. (2007). Technical Difficulties. The Wall Street Journal Online Edition, November 8, 2007. Retrieved November 8, 2007. Delaney, K., & Sharma, A. (2007). Google Has Even Bigger Plans for Mobile Phones. The Wall

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Street Journal Online Edition, November 16, 2007. Retrieved November 16, 2007. Farrell, J., & Weiser, P. (2003). Modularity, Vertical Integration, and Open Access Policies: Toward A Convergence of Antitrust And Regulation In The Internet Age. Harvard Journal of Law & Technology, 17(1), 85-134. Faulhaber, G. (2007). Network Neutrality: The Debate Evolves. International Journal of Communications, 1(1), 680-700. Federal Communications Commission (2005). Appropriate Framework for Broadband Access to the Internet over Wireline Facilities. Policy Statement, CC Docket No. 02-33, FCC 05-151. Federal Communications Commission (2007). High-Speed Services for Internet Access: Status as of December 31, 2006. Industry Analysis and Technology Division, Wireline Competition Bureau, October 2007. Frischmann, B., & van Schewick, B. (in press). Network Neutrality and the Economics of an Information Superhighway: A Reply to Professor Yoo. Jurimetrics, the Journal of Law, Science and Technology. Grant, P. (2006). Cable Industry May need to Spend Heavily on Broadband Upgrades. The Wall Street Journal, August 17. p. A1. Malik, O. (2007). 3Q 2007 Broadband Report Card: B-Minus. GigaOm, November 13. Retrieved May 8, 2008 from http://gigaom.com/2007/11/13/ 3q-2007-broadband-report-card-b-minus/. Mangalindan, M., & Rhoads, C. (2007). Sorry, Wrong Number, eBay Says on Skype. The Wall Street Journal, October 2, p. B1. Moritz, S. (2007). AT&T, EchoStar Deal Nears. TheStreet.com, November 19. Nuechterlein, J., & Weiser, P. (2005). Digital Crossroads. Cambridge, MA: The MIT Press.

Owen, B., & Rosston, G. (2003). Local Broadband Access: Primum Non Nocere or Primum Processi? A Property Rights Approach. Joint Center AEI-Brookings Joint Center for Regulatory Studies, 03-19, p.7. Peha, J., Lehr, W., & Wilkie, S. (2007). The State of the Debate on Network Neutrality. International Journal of Communications, 1(1), 709-716. Picker, R. (2005). SBC and Verizon: Judgment Day. The University of Chicago Law School Faculty Blog, November 3. Retrieved November 3, 2005 from http://uchicagolaw.typepad.com/faculty/2005/11/sbc_and_verizon.html. Reardon, M. (2006a). Qwest CEO supports tiered Internet. c/net NEWS.Com, March 16, 2006. Retrieved March 16, 2006 from http://news.com. com/Qwest+CEO+supports+tiered+Internet/210 0-1034_3-6050109.html. Reardon, M. (2006b). FCC approves AT&T-BellSouth merger. c/net NEWS.com, December 29, 2006. Retrieved May 15, 2008 from http://www. news.com/FCC-approves-ATT-BellSouth-merger/2100-1036_3-6146369.html. Schatz, A. (2007). FCC Deregulates Verizon’s Big-Business Market. The Wall Street Journal Online Edition, Retrieved March 21, 2007. Searcey, D. (2007). Cable’s Picture Gets Fuzzier. The Wall Street Journal, November 8, 2007. p. B3. Shwiff, K. (2007). Legal Costs Widen Vonage’s Loss. The Wall Street Journal Online Edition, Retrieved November 8, 2007. Sidak, G. (2007). What Is the Network Neutrality Debate Really About? International Journal of Communications, 1(1), 377-388. Swanson, B. (2007). The Coming Exaflood. The Wall Street Journal Online Edition, Retrieved January 20, 2007.

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Verizon (2007). Verizon Continues to Dramatically Raise Broadband Upload Speeds in FiOS Internet Service Area. Verizon News Release, November 20.

Federal Communications Commission: The United States federal regulatory body that oversees competition issues in the Internet service, telephone and cable television industries.

Weiser, P. (2003). Toward a Next Generation Regulatory Strategy. Loyola University Chicago Law Journal, 35, 41-85.

Net Neutrality: The decision by the Internet service provider to treat all content and applications equally in terms of distribution to the end user.

Werbach, K. (2002). A Layered Model for Internet Policy. Journal of Telecommunications & HighTechnology Law, 1(37), 58-64. White, B. (2007). Its Creators Call Internet Outdated Offer Remedies. The Wall Street Journal Online Edition, October 2, 2007. Retrieved October 2, 2007. Whitt, R. (2004). A Horizontal Leap Forward: Formulating a New Communications Public Policy Framework Based on the Network Layers Model. Federal Communications Law Journal, 56(3), 587-672. Yoo, C. (2005). Beyond Network Neutrality. Harvard Journal of Law & Technology, 19(1), 1-77.

KEY TERMS Convergence: The blending of three previously-distinct services: voice telecommunications, video (television) service and Internet access.

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Network-Layers Model: A model of a communications network that illustrates the distinction between content, applications, software and physical infrastructure. Telecommunications Act of 1996: A federal United States law that governs the regulation of telephone and cable companies. Triple Play Provider: A company that provides all three important communication services to a household: voice communication, video (television) and Internet access. Two-Tiered Internet: The decision by the Internet service provider to give some content or applications preferential treatment, for example by using faster transmission speeds.

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Chapter IX

International Internet Interconnection Service in Asia-Pacific Region Moon-Soo Kim Hankuk University of Foreign Studies, Korea

Abstract Since 1986, the Internet has developed into a global network enabling users worldwide to connect to each other to exchange information and data. The initial zero settlement peering arrangements, however, have now largely been replaced by commercial transit arrangements, as backbone providers seek to recoup their network infrastructure investments and generate commercial profits. This is a key cause of the issues and debates that have emerged between developed and developing countries about international Internet interconnection services (IIS). This study focuses on current interconnection settlement arrangement models that disfavor ISPs and end-users in the Asia-Pacific region. After reviewing the Internet market and digital divide in the region, the chapter summarizes the main current IIS issues between the AsiaPacific and Western regions into three categories of concern: inequity, anticompetitive practices and the threat of the “balkanization” of the Internet. Practical recommendations to resolve these issues and improve the Asia-Pacific IIS market are discussed from regional and international perspectives.

1. Introduction The Internet is commonly understood to be a worldwide network reaching beyond national borders. This worldwide connectivity, however, does not mean that there is one global network serving all regions across the world. Instead, this

connectivity is created by countless open-architecture networks of varying sizes, interconnecting to exchange information and data. The original free peering arrangement, however, has now been replaced by transit arrangements, as backbone providers have sought to recoup their network infrastructure investments and generate com-

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International Internet Interconnection Service in Asia-Pacific Region

mercial profits. Transit arrangements constitute a special problem for ISPs in the Asia-Pacific region with regard to their interconnection to American IBPs (or ‘backbones’) and ISPs from other regions, as such Asia-Pacific/US interconnections are provided under one-sided transit arrangements, which entail the full costs of such connections being borne by the Asia-Pacific region. This type of unilateral settlement arrangement seemed to make sense up until the 1990s, when most internet-related information was concentrated in the US, but this is no longer the case. ISPs in Korea and other Asia-Pacific countries have been paying excessive prices to IBPs in the US and other developed countries on the basis of such agreements, a situation that is exacerbating the digital divide between world regions. The Asia-Pacific countries officially challenged this inequitable cost-sharing arrangement at the third APEC TEL Working Group meeting in Singapore in 1998. During this meeting, a special taskforce (the International Charging Arrangement for Internet Service; ICAIS) was formed, and a resolution adopted to conduct research in this area1. However, investigating the internet connection market is far from easy, as details of interconnection arrangements are considered as purely commercial agreements which have been freely consented to by the parties involved, and are thus generally kept confidential. Typically, such contracts impose confidentiality not just as to their principal content, but also about pricing details and even the most general information. Challenges to research investigations also come from the sheer complexity of internet traffic, which makes it more difficult to design rational settlement models than, for example, for telephone networks. Efforts to resolve the imbalances in charging arrangement have thus so far failed to produce concrete results. This chapter, as a pilot study under the deficiency of the related data and previous studies, deals with the IIS (International Internet Interconnection Service) market, particularly, the current

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interconnection settlement arrangement which disfavors ISPs in the Asia-Pacific region, further is to give the alternative methods to resolve this issue by examining the debates among internetrelated experts and policymakers, reviewing other records containing the content of meetings of international organizations such as WTO, APEC, OECD and ITU-T, etc. The chapter is arranged as follows. Section 2 offers the various types of arrangements in its hierarchy of interconnection. Section 3 reviews the recent trends in the Asia-Pacific internet market from the perspective of the digital divide between the developed and developing countries, while section 4 examines several issues raised in recent years about interconnection services between the Asia-Pacific and Western regions. Practical recommendations designed to resolve these issues and to develop the Asia-Pacific IIS market are discussed in section 5. Finally, section 6 includes the summary and concluding remarks.

2. IIS and Interconnection Agreements The Internet is a network of computer networks operated by various ISPs using a universal protocol known as TCP/IP. Traffic exchange occurs both between ISPs located in different service geographic regions, and between those at different tiers of the internet connection hierarchy. Arrangements for physical interconnections between these ISPs may be distinguished into two broad categories: peering arrangements – which involves the cost-free transfer of data - and transit arrangements, where ISP s or IBP’s charge for such transfers. Thus internet connectivity is ensured via one or more of these peering and/or transit arrangements. IBPs forward traffic generated by both their own customers and subscribers to other ISPs on to outside regions, interconnecting with other IBPs to exchange data under connection agreements

International Internet Interconnection Service in Asia-Pacific Region

referred to as peering contracts. Peering arrangements generally occur between Autonomous Systems (ASs), usually held by IBP or big ISPs of equivalent size, or at least where both parties can see a mutual benefit (OECD, 2006). In reality, there are 3-types of peering: public peering, private peering and paid peering. Private and public peering are distinguished by the degree of openness of their interconnections, but generally involve free peering, an arrangement usually adopted when the two parties consider the amount of traffic from each sides to be roughly equal, thus making a settlement-free exchange more cost-efficient. Free peering is most often entered into between two ISPs of a similar size, and the arrangement is known as “bill-and-keep”, “settlement-free” or “sender-keeps-all” (this does not include special cases like paid peering). Public peering occurs at public access points or exchanges such as NAPs or Metropolitan Area Exchanges (MAEs) in the US. At these public access points, large numbers of networks exchange traffic using the so-called “hot-potato routing” method. Public peering is managed by public organizations, but as internet traffic volumes increased, NAPs serving as public peering points were affected by heavy congestion, and private peering emerged as an alternative to public peering. Private peering consists of directly connecting circuits between two large IBPs. Under private peering, there is no risk of information disclosure, as the exchange of traffic takes place on agreed terms at access points agreed between the ISPs. Private peering constitutes a crucial area for global internet and related traffic issues, providing as much as 80% of total US internet traffic (Elixmann & Scanlan, 2002). Lastly, Paid peering is used when two ASs (Autonomous Systems) agree that, on balance, one of the networks derives greater value from traffic exchange than the other. For example, ISP-A may have a lot of customers or attractive content, and ISP-B agrees to pay ISP-A so that its customers may have direct access to ISP-A’s

customers and content, although ISP-A will not carry third party traffic for ISP-B. A network such as the AOL Transit Data Network (ADTN) offers paid peering to other networks, allowing their customers the benefits of direct access to AOL Time Warner content as well as to their 35 million customers (OECD, 2006). If ISPs are unable to enter into peering agreements with other IBPs, they have to buy transit services from an IBP in order to provide their subscribers with universal access to the global internet. Transit is the term applied when one AS agrees to carry traffic for another for delivery to the rest of the Internet. Whereas peering only offers connectivity between the customers and content of two individual ASs, transit usually provides connectivity to the entire internet at a predictable price. Transit providers such as global IBPs, regional IBPs and big ISPs, etc charge for both basic and ancillary services, such as Service Level agreements, installation support, local telecommunication infrastructure provisioning and NOC (Network Operations Center) support. Transit arrangements are the most common interconnection model, and are vital in guaranteeing the Internet its global connectivity. Under such arrangements, an ISP wanting to send traffic to another ISP which has to be routed via a network owned by a third ISP must purchase a corresponding transit service. An ISP (or IBP) that sells transit services will receive packets that are not addressed to it as their final destination, and route them toward other ISPs with which they have peering relationships or, where they lack such arrangements, buy transit services to forward them. Transit can provide end-users of the Internet with a degree of connectivity which could never be possible via peering alone, and thereby enable ISPs to offer many more services. In sum, ISPs enable user access to worldwide internet address locations through a combination of peering and paid transit arrangements. When new IBPs providing transit services enter the market, they trigger price competition similar to

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that in any other market, which may bring down transit fees, perhaps to the level of connection fees. Meanwhile, from an IBP’s point of view, connecting with more ISPs means increasing their network effect, which also gives them an incentive to seek to lower transit fees.

3. The Asia-Pacific IIS market and the digital divide The Asia-Pacific region, home to 56.3% of the world population, accounted for about 38% of all internet users worldwide in 2004, a share which was projected to grow to 42% by 2007. This will make it the regional internet market with the largest number of subscribers and which generates the most traffic, as well as being the source of the biggest internet investment and offering the highest value-added potential. However the number of internet subscribers in the Asia-Pacific region amounts to only 8.3% of total regional population 2 in 2003, and there exists significant disparities of subscription rates between Asia-Pacific countries. This gap is explained by the difference in national

internet infrastructures, internet investment conditions and national levels of interest in using the Internet. In 2003, the three wealthiest of the 40 Asia-Pacific countries accounted for 28% of total internet subscribers in the region; with the nine countries in the medium-developed or upper-income country group accounting for 16%; and the remaining 28 countries for the final 56% (ITU-T, 2004). The disparity between Asia-Pacific countries is even wider in terms of broadband internet subscribers, where the 12 wealthiest Asia-Pacific countries account for an overwhelming 84% of the region’s broadband subscribers. These extreme imbalances in terms of internet usage are the main causes of the digital divide that exists between the region’s countries. Meanwhile, in terms of international internet traffic levels, the medium-developed or upper-income countries with a large number of broadband subscribers occupy a 58% share of total traffic. Also, the international internet traffic amount per capita among the 28 lower-income countries represent to less than 1% of the average. The remaining 12 countries account for over 99% of international

Figure 13. Shares of Internet and broadband internet subscribers by country Group in Asia-Pacific Region Distribution of Internet Subscribers in Asia-Pacific (2003) 70% 60% 50% 40% 30% 20% 10% 0%

lower income (28 countries)

upper income (9 countries)

Share of Internet Subscribers

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developed (3 countries) Share of Broadband Subscribers

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Figure 2. Internet Traffic Amount by Country Group in Asia-Pacific Region International Internet Traffic in Asia (2003) 120 .0

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International Internet Traffic (Gbps)

internet traffic, indicating the lopsidedness of the region’s internet usage. The chief cause of this considerable disparity in internet use within the region appears to be the high internet access price charged to end users, which is driven up by the absence of internet infrastructure and high price of international connections. In 2003, the average monthly internet access fee (based on 20 hours use per month)

developed (3 countries)

in the 28 lower-income Asian countries was 1.6 times that pertaining in the three wealthiest countries, which translates to being 88 times more expensive when these countries’ per capita income levels are factored in. There was also a sizeable difference between upper-income and lower-income countries in terms of internet access service pricing structures. In the former, flat monthly rates without set usage limits were the

Figure 3. Internet access price by country group in Asia-Pacific Region Internet Access Price in Asia by Country Group 30.0 25.0

80.0

20.0 60.0 15.0 40.0

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norm, whereas lower-income country users faced Figure 45 shows that, while international interseparate charges for excess minutes or hours, as connection prices have declined overall, the costs well as telephone charges and other additional fees, paid by Asia-Pacific ISPs are much higher than which obviously hinder local internet users. their European and US counterparts. InterconnecThis disparity at the level of the number of tion charges (referred to as upstream bandwidth internet users and traffic amounts is inevitably cost, see AfriISPA, 2002) make up the largest echoed in market size and investment. The fact element of most ISPs’ operating costs, as well as that the capital expenditure shares of China and a considerable portion of the internet access fees other Asian countries exceed those of their revenue paid by end-users in emerging Asia-Pacific counby far is encouraging for the regional telecom tries. According to Antelope (2001) the share of industry. Meanwhile, the size of the internet ISP costs accounted for by international internet backbone market of the Asia-Pacific region is transit charge, which (while varying quite widely nevertheless expected to reach only a size corfrom country to country) was estimated in 2001 responding to 50% of that of Europe and North as approx. 30% on average. America by 2007 (RHK Inc. 2003). Notably, the This considerable cost burden is a main factor fact that the monthly traffic levels generated in behind Asian complaints as to the inequity and Asia-Pacific during 2004 were about equal to unfairness of their current international transit 4 that in Europe suggests that the Asian backbone agreements with US and European IBPs. If the market is less competitive than its European and digital divide among Asia-Pacific countries is to be North American counterparts. This inequality in reduced by increasing investment and promoting turnover, on the other hand, explains why Asian diffusion of internet accessibility, it is seen as crubackbone providers have continued to have to cial that ways are found to lower the international purchase transit services from European or North transit costs that make up such a large portion of American providers, rather than being able to the region’s ISP’s operating budgets. enter into peering relationships as equal partners. This analysis of internet trends in the AsiaMeanwhile, the European backbone market is Pacific region highlights the following general expected to roughly equal the size of its North points. First, the rapid increase in internet users’ This considerable cost burden is a main factor behind Asian complaints as to the inequity and American counterpart, evolving along a differnumbers and traffic levels has only worsened the unfairness of their current international transit agreements with US and European IBPs. If the digital ent path than the Asian market, despite the later problem of disparity between the region’s coundivide among Asia-Pacific countries is to be reduced by increasing andispromoting diffusion generating about the same amount of traffic. tries, investment and this gap even wider in theofbroadband internet accessibility, it is seen as crucial that ways are found to lower the international transit costs that make up such a large portion of the region’s ISP’s operating budgets.

Figure 4. International Internet lease price, US cents/Mbps,Mile STM-1 Monthly Lease Price/Mbps,Mile (Transoceanic Cable)

T-1 Monthly Lease Price/Mbps,Mile (Transoceanic Cable)

  86FHQWV

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 /RQGRQ 1HZF R2 Adj. R2

Note: *significant at 90% level; ** significant at 95% level; *** significant at 99% level. (dependent variable MVNO penetration from 2004 to 2005, t-static in italics)

A Techno-Economic Analysis of Mobile Virtual Network Operators

by HHI) shows a positive effect, but is not statistically significant on MVNO penetration. This finding contradicts a widely held belief exhibited in several previous studies (e.g., Noam, 2003b) that HHI is a standard indicator of concentration. The HHI of the U.S. is more effective than Europe. The HHI of the U.S. is 1,377 compared to that of Europe. Market concentration is low by international standards in the U.S., and the MVNO penetration, therefore, has been largely unaffected by market concentration. Concentration also is not a significant factor in Asia. For example, Hong Kong’s HHI is low (1,936), but is an effective HHI figure. The HHI figures of the Asian countries contribute to the insignificant result of competition and concentration. As the competition variable shows, Hong Kong and Singapore are two of the world’s most competitive mobile markets. The implication is that the Asian markets in general are small-scale markets, and therefore the incentive to innovate may be lower than in large markets. As shown in the EU and the U.S. mobile markets, larger firms innovate more. The largest operators in Hong Kong and Singapore have relatively small market shares. These cities host two of the most fragmented world markets, and less fragmented markets, such as the EU and the U.S., have much higher MVNO penetration. An explanation may be that fragmentized or segmented submarkets in smaller overall markets obviate inter-operator collaboration on application development (Godfrey & Kam, 2004). As to the HHI variable itself, it may not be a good measure in such a small market (Farrell & Shapiro, 1990; Demsetz, 1974). A more appropriate measure may be Gans’ new measurement of HHI when it involves vertical structure, namely “vertical HHI” (Gans, 2005). The market segmentation variable shows different results across groups. The segmentations in EU and North America show a significant correlation with the MVNO market share. This result reflects the current U.S.’s MVNE proliferation: there are more than 25 MVNE in the U.S.

(Pyramid Research, 2006). An MVNE does not have a relationship with end-user customers. Instead, MVNEs provide infrastructure and services to enable MVNOs to offer services and have a relationship with end-user customers. MVNEs enable infrastructure and related services, ranging from network element provisioning, administration, operation support systems, and business support systems, by providing intermediation between MVNOs that do not want to have any control over network elements and those that want complete control. As of 2006, there are more than 39 MVNE’s in the world; eighty percent of them are located in Western countries, and there is no MVNE in Asian countries (Pyramid Research, 2006). MVNEs accelerate market segmentation by allowing MVNOs to provide various segments such as prepaid, high-end, data-focused players, etc. Interestingly, this segmentation variable shows a significant correlation with the vertical integration variable. This can be explained by the fact that the European MVNE’s provide the telecom operators with a relationship to manage the ability to manage relationships through a single, trusted interface for different MVNOs (Kristensson, 2001). In other words, MVNE’s provide a bundled platform for MVNOs. These equate to turnkey type solutions that typically include automated interfaces to a carrier’s provisioning system, real-time or near-real-time usage, and gateways for Short Message Service and content, as well as the usual Telco back-office systems and services. MVNEs take such forms as Application Service Providers, billing companies, content providers, hardware manufacturers, and Internet or media companies. It can be said that MVNOs and MVNEs are motivated by the same factors but the latter influences the MVNO penetration (Shin & Bartolacci, 2006). The highly vertically integrated markets in Asia have generally not been favorable to the MVNO model. The fact that the MVNO model has had difficulty establishing itself in such segmented

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market environments suggests that the intensity of the facilities-based competition creates limited opportunities for them to be economically viable, even with differentiated strategies in the face of aggressive price competition. In regard to market performance, the ARPU variable shows no significant correlation, although it does show a positive correlation. The insignificance of ARPU implies that the main challenge prospective MVNOs will face is not necessarily a low ARPU, but other challenges such as a niche market. In other words, regardless of whether mobile operators are making or losing profit, they are seeking new markets. As Jost (2004) predicts, MVNOs can potentially survive on $5 ARPU, but the MVNO model in general must find a way to survive on the cost side of the business. The positive relation implies that MVNOs are active in markets where they deal with low margin subscribers. The undesirable role of MVNOs in this scenario protects the host carrier from undesirable financial costs such as those related to volatile prepaid churn, high capital investment, and consumer fraud. All of these can accompany an MVNO that targets low-value subscribers. The positive correlation further suggests that MVNOs must find a niche among incumbent carriers who are willing to lease capacity, since most operators are unlikely to open their networks. The estimation results of liberalization show that liberalization is a somewhat significant factor (Table 3). It is interesting to note that the Asian markets’ liberalization also significantly contributes to MVNO penetration (Table 4), despite the low penetration in general. Since the market liberalization in the EU, a huge number of competing MVNOs are operating, while in Asian markets, under pressure of regulations and entrepreneurs, the process of MVNO development has just started. This can be interpreted that several Asian countries like Japan, Malaysia, and India are making positive efforts to facilitate MVNOs by establishing guidelines requiring network operators to lease or remain open to MVNOs.

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The contradiction between liberalization and low MVNO penetration in Asian countries also can be explained from the different nature of liberalization. Asian countries in general achieved liberalization in policy and regulation, but actual markets seem not to fully feel such liberalized environment (Chowdary, 1998). While the liberalizations in Western countries have been achieved in an autonomous interaction between government and market, Asian countries seem to achieve it solely by policy-driven liberalization (Shin, 2007). The liberalization indicators in Asian countries may be policy-based, which is different from the market-based liberalization of Western countries. Under the policy-based liberalization, the markets are artificially changing toward liberal markets, but liberalized markets are most effective in climates of effective competition (Wu, 2003). Although overall Asian markets are apparently liberalized by government intervention, Asian markets still seem to be not liberal enough to embrace the MVNO, and the MVNO does not appear to stabilize in markets without effective competition. Overall, the empirical analysis does show key drivers of MVNO penetration, but it also implies that several constellations of factors can be conducive to MVNO penetration. The active operation of MVNEs supports the analyses of segmentization, vertical integration, concentration, and liberalization. This point needs to be further examined by using panel regression.

5. Conclusion The emergence and proliferation of MVNO is not simply matter of infrastructure sharing between HNO and MVNO. It may involve a more fundamental question of market condition as the emergence of MVNOs has revealed two main industry structures in the mobile telecommunications industry: a horizontally layered (either diversified or consolidated), market-driven

A Techno-Economic Analysis of Mobile Virtual Network Operators

structure with a modular product architecture, and a vertically integrated, walled-garden oligopoly with an integrated product architecture. As shown previously, MVNO services are much more successful in Western than in Asian countries. One major reason for this difference in success is the differences in the industry structures between the markets in both areas. Because of the complexity of MVNOs, a horizontally layered structure seems to be more inviting. This finding provides future carriers and potential MVNOs with a framework to determine whether or not the MVNO model is right for their respective business. MVNO services are more successful in markets where virtual operators take intermediary and aggregating roles in order to offer a true end-to-end mobile service. The incumbent Asian operators are not eager to change the market structure. It seems that MVNOs would reap nothing but negative consequences from the consumer’s point of view if the market structure changed. In his study on market structure, Economides (1996) leaves open the question of whether the horizontal or a vertical industry structure is better for MVNOs. That is, the open questions would be: Is it more valuable to have a transparent, marketdriven industry structure or a vertically integrated oligapoliy enabling the provision of easy-to-use services? Would this more integrated structure provide a mobile telecommunications market with only one, monopolistic player. This study partly answers such questions by showing that a horizontally-layered market is better at facilitating MVNO penetration. It appears that the vertically integrated telecom business models are less effective in an environment where the demand for a whole range of value-added services is strong. Under such a horizontal value chain, vertical integration seems to be minimized. Predicting which MVNO trends will prevail can be a hard question. In the long run, MVNOs, along with MVNEs, are likely to rise and decline in popularity as uncertain markets and industries and change. One thing is clear that regardless of whether MVNOs, prevail

or fail, their impact will be significant throughout the wireless industry.

6. Limitations and future studies Given its complexity, defining telecom market structure is always elusive and difficult. This study is an exploratory attempt to define mobile market structure to analyze the emerging phenomena of the MVNO. For parsimony, the study neglected various issues like the differences between the service demand scenarios in different countries and the maturity of the market. In addition, this study used an aggregation model, and data were collected for the limited time of 2004-2005. Therefore, it would be helpful in the future to conduct comparative studies at a less aggregated level, such as using cross-sectional and time-series analysis methods. In addition, multivariate regression, as Cava-Ferreruela et al. (2006) indicate, has weak numeric and estimation features. Other sophisticated measures may be accompanied with multivariate regression, such as bootstrap re-sampling or stepwise selection techniques. Furthermore, it is not desirable to set a linear relation between the dependent variable (MVNO penetration) and independent variables in this study, because the relation may not linearity. The relation, however, can be natural log (non-linearity). Using natural log of non-linearity, the analysis will be smoother and produce better ideas. Future studies may complement the nonparametric local polynomial regression techniques to the existing parametric regression model. Although the relation may not be quite linear, the existing parametric regression analysis is worthwhile to keep for comparison to the non-parametric, given that the relation can be largely used in other studies in telecommunications. Using both parametric and nonparametric regression, theoretical robustness can be increased. In addition, a strong conceptual

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framework will better predict the prospect for MVNOs. The current study intentionally simplifies and limits the variables in order to grasp an overall understanding of MVNO penetration factors. The limited variables allowed this study to set aside regulations, and policy, and carrier conduct and behavior as dummy variables. As Economides (1996) argues, the structural differences are caused by dissimilarities in the national regulations. As the present study excludes national policy from variables, it neglects to note many important aspects: EU regulators are opening up network access in favor of MVNO models and the FCC has been generally favorable to MVNO, which is not the case in non-Western regions. In addition, the significant results of the dummy variable imply that there is something more behind MVNO penetration and market structure. For example, despite the overall similarities between the U.S. and the EU, the lower MVNO in the U.S. can be explained by the fact that the U.S. operators are carefully watching MVNO development because they believe that the transition period between 3G and 4G will be the most fruitful period for MVNOs. This kind of carrier behavior will have to be investigated with respect to regulation and policy.

References Bauer, J., Kim, J., & Wildman, S. (2005). Effects of national policy on the diffusion of broadband in OECD countries. The UFL-LBS Workshop of the Future of Broadband: Wired and Wireless. Gainesville, FL, February 24-25, 2004. Boylaud, O, & Nicoletti, G. (2001). Regulation, market structure and performance in telecommunications. OECD Economic Studies, 32, 99-142. Capuano, C. (2005). Access regulation in vertically integrated oligopolies. Proceedings of 32th

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the European Association for Research in Industrial Economics (EARIE) Conference. Cava-Ferreruela, I., & Alabau-Munoz, A. (2006). Broadband policy assessment: A cross-national empirical analysis. Telecommunications Policy, article In Press. Choi, C., & Shin, H. (1992). A comment on a model of vertical product differentiation. The Journal of Industrial Economics, 40 (2), 229-231. Doyle, C., & Smith, J. C. (1998). Market structure in mobile telecoms: qualified indirect access and the receiver pays principle. Information Economics Policy, 10(4), 471-488. Economides, N. (1996). The economics of networks. International Journal of Industrial Organization, 14(2), 675-699. Farrell, J., & Shapiro, C. (1990). Horizontal Mergers: An Equilibrium Analysis. American Economic Review, 80(1), 107-123. Gans, J. S. (2005). Concentration-based merger tests and vertical market structure. Journal of Economic Literature, 43(2), 238-256. Godfrey, J., & Kam, J. (2004). What it takes to kick start mobile data: the lessons from Japan and South Korea. ITU Asia 2004, Online News Service. Gual, J., & Trillas, J. F. (2004). Telecommunications policies: determinants and impact. (August 2004). CEPR Discussion Paper No. 4578. Available at Social Science Research Network: http://ssrn. com/abstract=604468 Hodendorn, C. (2005). Regulating vertical integration in broadband: Open access versus common carriage. Review of Network Economics, 4(1), 19-32. Hoekman, B. (1995). Trade laws and institutions: Good practices and the World Trade Organization. Supplementary paper presented at The Uru-

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guay Round and Developing Economies, a World Bank Conference, 26-27 January 1995. Informa Research (2005). Informa research services’ telecom market segmentation and customer profiling program. Accessed in March 2006 http://www.markettrends.com/industry/telecom/ telecomproj.htm#5 International Telecom Union (2001). Mobile Virtual Network Operators. Geneva. Geneva: ITU. International Telecom Union (2004). Trends in telecommunication reform: Effective regulation. Geneva: ITU. International Telecom Union (2002). Asia-Pacific Telecommunications Indicators. Geneva: ITU. Jang, B. (2003). Vertical structure and network competition in telecommunications services market. Information Society Research, Fall: 81-101. Jost, J. (2004). Can MVNOs succeed in emerging markets? Pyramid Research. Krafft, J. (2003). Vertical structure of the industry and competition: an analysis of the evolution of the info-communications industry. Telecommunications Policy, 27(8/9), 625-649. Kristensson, S. (2001). Mobile Virtual Network Operators. Assessing MVNO business opportunities. School of Business, University of Stockholm, Master of Science Thesis, June 2001. Lehr, W. (2002). Vertical integration, Industry Structure, and Internet Telephony. In McKnight, Lehr, and Clark (Ed.), Internet Telephony. The MIT Press. Li, W., & Xu, L. C. (2002). The political economy of privatization and competition: Cross-country evidence from the telecommunications sector. Journal of Comparative Economics, 30(3), 439462. Melody, W. (1999). Telecom reform. Telecommunications Policy, 25, 7 – 34.

Noam, E. (2004). The Internet: Still Wide Open and Competitive? Oxford Internet Institute, Internet Issue Brief No. 1, August 2003. Noam, E. (2003). The effect of deregulation on market concentration: an analysis of the Telecom Act of 1996 and the industry meltdown. The Columbia Science and Technology Law Review, 4, 1-12. Noam, E. (2003b). Deregulation and market concentration: An analysis of post-1996 consolidations. Federal Communications Law Journal, 58, 539-550. Noam, E. (2002). How telecom is becoming a cyclical industry, and what to do about it. Presentation at Columbia Institute for Tele-Information, Conference on Telecommunications Volatility, April 2002, Columbia University, New York. OECD Economics Department Working Papers (2001). OECD Economics Department in its series by Olivier Boylaud and Giuseppe Nicoletti. Regulation, market structure and performance in telecommunications, 2001. OECD (2004). Performance Indicators for Public Telecommunication Operators. Paris. Original OECD report available online at: http://www. oecd.org/dsti/sti/it/cm/prod/ICCP22.htm Ovum (2006). Virtual Mobile Services: Strategies for Fixed and Mobile Operators. Ovum Ltd. 2006, by John Matthews, Susan Sweet. http://www. ovum.com. Pyramid Research (2006). MVNOs and MVNEs: Analyzing the Viability of Virtual Mobile Players. February 2006 (ID: PYR1224156) Accessed in August 2006. http://www.marketresearch.com/ product/display.asp?productid=1224156 Sappington, D., & Weisman, D. (1996). Designing incentive regulation for the telecommunications industry. MIT Press, Cambridge, MA.

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Shin, D. H., & Bartolacci, M. (2007). A study of MVNO diffusion and market structure in the EU, US, Hong Kong, and Singapore. Telematics & Informatics, 24, 86-100.

Horizontal Markets: Two markets are horizontally related if the two goods in question are substitutes or complements in production or consumption.

Shin, D. (2007). A critique of Korean national information strategy: case of national information infrastructures. Government Information Quarterly, 24(3), 624–645.

MVNO (Mobile Virtual Network Operator): A company that provides mobile phone service but does not have its own frequency allocation of the radio spectrum, nor does it have all of the infrastructure required to provide mobile telephone service.[

Ulset, S. (2002). Mobile virtual network operators: a strategic transaction cost analysis of preliminary experiences. Telecommunications Policy, 26(9-10), 537-549. Wireless Asia (2002). Virgin Mobile and SingTel jointly call off their Virgin-branded MVNO mobile service a mere eight months after its launch. August 21 2002. Wu, F. (2003). From monopoly to competition: a comparative study of telecommunications policy reform in four Asia countries. Proceeding of Pacific Telecommunications Council, January 2003, Manoa,Hawaii.

key terms ARPU (Average Revenue Per User or Average Revenue Per Unit): This term is used by telephone carriers. This term has also become widely used in other industries including consumer Internet service providers. It is the revenue generated by a customer phone, pager, etc., per month. Herfindahl-Hirschman Index (HHI): A commonly accepted measure of market concentration. It is calculated by squaring the market share of each firm competing in a market, and then summing the resulting numbers. The HHI number can range from close to zero to 10,000.

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MVNE (Mobile Virtual Network Enabler): A MVNE does not have a relationship with end-user customers. Instead, a MVNE provides infrastructure and services to enable MVNO’s to offer services and have a relationship with end-user customers. Vertical Integration: A style of ownership and control. The degree to which a firm owns its upstream suppliers and its downstream buyers determines how vertically integrated it is. Vertical Market: A vertical market is a particular industry or group of enterprises in which similar products or services are developed and marketed using similar methods (and to whom goods and services can be sold).

Endnote 1



ARPU is the revenue generated by a customer phone, pager, etc., per month. In mobile telephony, ARPU includes not only the revenues billed to the customer each month for usage, but also the revenue generated from incoming calls, payable within the regulatory interconnection regime.

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Chapter XI

Evolving Value Networks and Internationalisation of National Telecommuncation Companies from Small and Open Economies Riku Laanti The University of Adelaide Business School, Australia Fred McDougall The University of Adelaide, Australia Georges Baume The University of Adelaide Business School, Australia

Abstract This chapter focuses on the internationalisation processes of national telecommunications companies (telcos) from small and open economies (SMOPECs) who have moved from a domestic monopoly to an actor within the global industry. This chapter aims to increase our understanding of how these companies have internationalised, what factors have been the most influential in this process, and how the position of these companies has changed in the evolving value network of the industry. The basis of the analysis will be a theoretical discussion about the concept of value networks and research on the internationalization process of a firm. The study reported in this chapter is part of a wider research project on the internationalisation strategies of telcos from SMOPECs. Case examples from that study will be used to illustrate the internationalisation processes of telcos from SMOPECs within the context of the whole industry value network. Finally, conclusions will be drawn and future research opportunities suggested.

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Evolving Value Networks and Internationalisation of National Telecommuncation Companies

INTRODUCTION The telecommunications industry has experienced significant transformation: value chains have changed from vertical to horizontal, and there has been an important shift from value chains to value networks (Cave & Waverman, 1999; Fjeldstad, Becerra, & Narayanan, 2004; Li & Whalley, 2002; Sabat, 2002; Steinbock, 2003). Many factors, such as digitalisation, deregulation and privatisation, have contributed to these developments (Häikiö, 2001; Ramamurti, 2000). Li and Whalley (2002), who explored the complexity of value networks, argued that new research is needed in this still evolving area. They emphasized that ”To survive and thrive in this new environment, every company needs to understand their positions in each of the value chains within the value network, and to re-evaluate their strategies and business models” (Li & Whalley, 2002, p. 469). This chapter will analyse these developments by focusing on the internationalisaton processes of national telecommunications companies (telcos) from small and open economies (SMOPECs), who have moved from a domestic monopoly to be an actor within the global industry. SMOPECs include countries such as Austria, Denmark, Finland, Ireland, New Zealand, Portugal, Norway, Sweden, and Switzerland, who have integrated in the world economy by lowering or eliminating their trade barriers (Benito, Larimo, Narula, & Pedersen, 2002; Kirpalani & Luostarinen, 1999; Maitland & Nicholas, 2002; Merrett, 2002). Multinational companies (MNCs) from smaller countries face specific challenges due to their relatively smaller size and limited resources, especially in capital-intensive service industries such as in the telecommunications industry. In these types of industries where expensive foreign direct investments (FDIs) are commonly the mode to enter international markets, the largest MNCs from the largest economies of the world often

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dominate the sector (Knight, 1999). Research findings are still limited on how MNCs from smaller countries have managed these challenges and if there are alternative strategies available for them internationally (Knight, 1999). This chapter aims to increase our understanding of how these companies have internationalised, what factors have been the most influential in this process, and how the position of these companies has changed in the evolving value network of the industry. An analysis of telcos from SMOPECs provides valuable longitudinal empirical data on this topic, as many of these companies were among the first telcos to internationalise. The study described in this chapter is part of a longer ongoing research project on the internationalisation of telcos from SMOPECs (Laanti, 2008). The purpose of the project has been to analyse the applicability of traditional internationalisation theories, especially internationalisation process theories and the latest strategic theories on globalisation, to a service network industry. Case examples from the empirical data of the wider study will be used here to illustrate the different phases of the internationalisation process of telcos from SMOPECs within the context of the whole industry value network. The findings described here should be useful to researchers and managers of internationalising telcos from SMOPECs, and telcos more generally, for other companies in the telecommunications industry or the whole ICT industry’s value network, and for policy makers to increase their understanding of the internationalisation process and associated factors. The next section focuses on the concepts of value chain and value network, and discusses the telecommunications industry´s value network and telco’s position and role in it. It is followed by a brief review of the research on internationalisation theories, with a more specific description and analysis of the internationalisation process

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of telcos from SMOPECs. Finally, conclusions are drawn and future research opportunities suggested.

FROM VALUE CHAINS TO VALUE NETWORKS Research on Value Networks The concept of value chain has been widely covered in the strategic management literature, most notably by Porter (1985). A value chain arises from a company’s activities and internal business processes to create value for its customers (Porter, 1985). This company specific value chain also belongs to a broader industry value chain or system (Porter, 1985). A company must recognise its most important value chain activities, how to add most value for its customers as well as how to manage its more generic value chain activities. To do this, managers must understand both the external environment, including industry value systems and customers, and the key internal resources and core competences. However, although these first studies on value chain recognised the importance of the external environment of a firm, they did not have their focus on the international aspect and impact of value systems. Recent developments in the telecommunications industry, not least due to globalisation developments, have seen value chains moving from vertical to horizontal, and from value chains to value networks (Li & Whalley, 2002; Sabat, 2002). The difference in the definition of value networks, when compared to the traditional definition of value chains, is that in a value network there are several entry and exit points, and that activities take place simultaneously, instead of successively (Li & Whalley, 2002). Fjeldstad et al. (2004) argued that value network models are especially successful in describing the business operations of companies such as telcos, which use mediating technologies.

The Telecommunications Industry’s Value Networks within a Single Country Two notable developments in the telecommunications industry have occurred. First, value chains started to disintegrate from a monopoly situation, in which they were highly vertically integrated (Contractor & Lorange, 2002; Economides, 1996; Glachant, 2002). Historically, national telecommunications industries were dominated by monopoly telcos, which basically operated the whole value chain from R&D, to equipment manufacturing, to network operating, to service operations, to the sales of the telecommunications equipment to the end-customers. A well documentend example is AT&T in the US (Fransman, 2002).1 However, deregulation developments gradually opened competition and monopolistic value chains started to disintegrate including more independent players. Competition increased in the equipment manufacturing/supply side to telcos and in the sales of equipment to the end-customers, and finally in the actual telco operations as well. This resulted in shifts up and down the value chain. Second, convergence across the telecommunications, IT, and media industries has caused value chains to integrate horizontally (Sabat, 2002), resulting in a new and broader definition for the whole industry - the information and communications technology (ICT) industry. Also, new significant services were developed, notably Internet and mobile communications. All these developments changed radically the operating environment of traditionally monopoly-based telcos. They faced challenges in the form of competition and at the same time new opportunities arose in new business areas. While existing players repositioned to new and more focused business areas, new entrants also emerged in the ICT ecosystem (Sabat, 2002). These included software developers, new infrastructure suppliers, and content and service

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Figure 1. Vertical integration of value chains into value systems (adapted from Steinbock (2003)) Monopoly

Network Operators

Equipment Manufacturers

Great Transition

Contract Manufacturers

Competition

Contract Manufacturers

Network Operators

Equipment Manufacturers

Equipment Manufacturers

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providers, such as banking by mobile and over Internet systems, mobile and online games, and videos and other information services (Peppard & Rylander, 2006). Opportunities emerged for the players who were able to identify and utilise the ‘sources of value in the network’ (Peppard & Rylander, 2006, p. 139). To demonstrate this progress in the wireless technology industry, Steinbock (2003) defined three different development phases: monopoly, great transformation, and competition (see Figure 1). In the monopoly phase, the whole value chain was operated by one company, a national monopoly telco. During the great transformation, though, independent equipment manufacturers started to take a more important role2. In the competition phase, the value chain disintegrated even more and the relative importance of the national telcos decreased significantly. Similar developments could be seen in other business areas in the industry, such as data communications. This new competition brought challenges to ex-national monopoly telcos, as their share of the total revenues and market shares of each individual part of the business started to shrink considerably. They were able to compensate this at some

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Application Software

Content

Network Operators

Service Operators

Operators?

level by entering new rapidly growing business areas such as mobile and Internet. However, they were also forced to start looking for new growth opportunities across their national borders.

INTERNATIONALISATION DEVELOPMENTS As aforementioned, increasing competition in the domestic markets acted as a push force for telcos to look for growth opportunities internationally. Moreover, globalisation developments opened foreign markets and made it easier for companies to internationalise. In the 1980s and 1990s globalisation seemed to be a fad in management research and practice, which may have put further pressures on telcos to internationalise. Research on internatonalisation has been covered in both the strategy and international business literature. Moreover, in international business two separate research streams have studied firms’ internationalisation, namely the economic and process streams (Benito & Welch, 1994; Liesch et al., 2002). In this chapter, the focus is on process theories, although findings are also

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drawn from the economic stream and from the strategy literature. Most traditional theories on the internationalisation process of a firm (Johanson & Vahlne, 1977; Johanson & Wiedersheim-Paul, 1975; Luostarinen, 1979, 1994) are based on research conducted on manufacturing MNCs. These process theories suggest that firms start their internationalisation by entering foreign markets with small psychic distance; that is, cultural and geographically close countries (Johanson & Vahlne, 1977; Johanson & Wiedersheim-Paul, 1975). Also firms start their internationalisation with less-committed operation modes, such as export, before committing more resources by investing in foreign markets. The process is linear and eventually develops into a global strategy by a MNC (Gabrielsson & Gabrielsson, 2004). In the 1980s and especially in the 1990s, globalisation was one of the major topics of research in management studies. Several researchers argued that companies need to go global as consumer tastes and markets converge rapidly (Levitt, 1983; Ohmae, 1989). Yip (1989; 2000), in his seminal works on globalisation strategies of companies, classified globalisation drivers into four major groups: cost, market, competitive and governmental drivers. Within manufacturing sectors some of the key drivers identified were cost drivers such as economies of scale in R&D and production, and sourcing materials; and market drivers such as searching for new customers in foreign markets. For example, to balance escalating R&D costs, manufacturing companies need to achieve greater sales volumes, thus needing to deliver products outside of domestic markets. This need to internationalise seems to be most evident for manufacturers from smaller countries with limited domestic demand (Steinbock, 2003). Another way to analyse the internationalisation process is to focus on organisation strategies. Bartlett and Ghosal (1992) argued that firms’ strategies develop from domestic, to interna-

tional, to multinational, to global, and finally to transnational. International strategies relate to companies which mostly export their products overseas without investing in significant foreign operations. Multinational strategy treats each country organisation individually, whereas in a global strategy operations are strandardised and centrally managed. Transnational strategies try to combine the ability to adapt locally, but to draw resources and share knowledge globally. Telecom equipment manufacturing companies seem to fit nicely into these theories, as they first started to internationalise incrementally, often by exporting their products, but soon established production facilities internationally. Also, these large MNCs seemed to implement global strategies relatively rapidly (Steinbock, 2003). However, there are several challenges to these traditional theories, such as the internationalisation of born global companies and service internationalisation. Even within the same industry, these very different types of companies have followed different strategies in their internationalisation.

Born Global Companies A group of companies that have challenged many traditional internationalisation theories are born globals. They are often small companies which, despite limited resources, are able to internationalise very rapidly, often to countries with large psychic distance (Knight & Cavusgil, 1996; McDougall, Shane, & Oviatt, 1994; Rennie, 1993). To manage this rapid internationalisation born globals often follow international/global niche strategies. Also, in many cases digitalisation and the use of Internet has been a major factor enabling this rapid internationalisation process for these companies (Laanti, Gabrielsson, & Gabrielsson, 2007). In the ICT sector many small but rapidly internationalised application developers and content providers could be labelled as ‘born globals’.

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Service Internationalisation Another challenge to traditional internationalisation theories that has attracted debate among researchers has been the internationalisation of services. Several researchers have argued that there are a number of significant differences in how services and manufacturing companies internationalise (e.g. Brouthers & Brouthers, 2003; Contractor & Kundu, 2000; Erramilli & Rao, 1993). First, service companies started to internationalise much later than most manufacturing companies. This was partly due to the different treatment of services in the world economy, as it was not until the Uruguay round of GATT negotiations in 1993, and the subsequent lowering of trade barriers for services, that resulted in a growth in services trade (Clark, Rajaratnam, & Smith, 1996; Javalgi, Griffith, & White, 2003). Second, many services have followed their industrial clients abroad, resulting in follow-thecustomer strategies, with more rapid processes than traditional theories would suggest (Majkgård & Sharma, 1998; Roberts, 1998). Third, services also possess several unique characteristics, which may cause them to be more challenging to internationalise than goods. Researchers have identified characteristics such as intangibility (Boddewyn, Halbrich, & Perry, 1986; Clark et al., 1996; Erramilli, 1990; Javalgi et al., 2003), inseparability (Erramilli, 1990; Javalgi et al., 2003), heterogeneity (Erramilli, 1990; Knight, 1999), and perishability (Erramilli, 1990; Lovelock & Yip, 1996). Thus, given the previously mentioned, ‘exporting’ as an operation mode may be infeasible in many service sectors (Erramilli, 1990; Javalgi et al., 2003). Four, services are also very heterogeneous, which means that there are also differences across different service sectors in regard to their internationalisation strategies. Thus, several researchers have also classified services based around their business processes and service characteristics, such as Erramilli’s (1990) hard- and soft-ser-

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vices; Boddewyn et al.´s (1986) three categories of foreign-tradable services, location-bound services, and combination services; and Clark et al.’s (1996) contact-based services, vehicle-based services, asset-based services, and object-based services. For example, using Erramilli’s classification a music-CD is a hard-service and is thus more easily exportable than a concert which is a soft-service.

Telco Internationalisation Most services that telcos provide are similar to many other network industries, such as utilities and railways; that is, a physical network is required before the service can be provided (Economides, 1996; Shy, 2002). Thus, it can be argued that these services are mostly soft-services, asset-based and/or location-bound services. Moreover, in the telecommunications service industry there were also several characteristics typical of these and other network industries such as network externalities and the strong role of government (Economides, 1996; Liebowitz, 2002; Shapiro & Varian, 1999; Shy, 2002). Also Yip (1989), in his research on globalisation, emphasized that in services the role of governmental drivers is much greater than in manufacturing industries. All this means that the logic in the internationalisation strategies for telcos may vary significantly from that for manufacturing companies (Sarkar, Cavusgil, & Aulakh, 1999), or for a service which is more closely related to goods, such as a hard-service. Following this reasoning, telcos have not been able to follow similar internationalisation processes to telecommunications manufacturers or to that of many ‘born globals’. This also supports the findings of several other researchers (see e.g. Lovelock & Yip, 1996; Majkgård & Sharma, 1998), who argued that different industries follow different internationalisation paths, and research on internationalisation should pay more attention to idiosyncracies and context specifity. In this context, Laanti et al.

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

(2006) developed a framework to analyse internationalisation strategies of telcos (see Figure 2). In this framework, five major groups of factors that influence internationalisation strategies were identified: globalisation factors, industry specific factors, home country specific factors, company specific factors, and host country specific factors. It was argued that there may be significant differences in how companies internationalise, based on differences in these factors. The focus of this chapter is on industry specific factors, and also on home country specific factors. The study that forms the basis of this chapter is focused on telcos from SMOPECs, and the influence of these factors on the internationalisation strategies of telcos. Research with a focus on the internationalisation process of telcos is still relatively sparse. Some important studies were undertaken by Sarkar et al. (1999) and Stienstra et al. (2004). Sarkar et al. argued that telcos’ internationalisation process is very unique due to three factors: the industry’s

oligopolistic structure, network characteristics, and limited opportunities available in foreign markets. This results in very opportunistic behaviour at the very early phase of the process. This was supported by the findings of Stientra et al., that telcos followed ‘herd-behaviour’ in the early internationalisation phase, but later started to make more strategic choices. However, these studies were focused largely on the internationalisation of the largest telcos and have not included some of the most recent developments in the industry. Thus, more information on the process is still needed. As mentioned earlier, due to the capital intensity of the industry, telcos from smaller countries faced even greater challenges in their internationalisation. Whereas the largest telcos from the largest countries started to compete in global markets and had sufficient resources to enter several of the largest markets with FDIs, SMOPEC telcos were forced to look for alternative strategies. These largest telcos

Figure 2. Conceptual Framework: Internationalisation strategies and factors influencing them Globalisation factors Industry specific factors Home country specific factors Company specific factors

Internationalisation strategies Manufacturing Companies Business Service Companies Retail Service Companies Born Globals (Manuf.&Service) Network Service Companies

Product strategy Operation strategy Market strategy

Host country specific factors

Organisation strategy

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were companies such as AT&T, Britisth Telecom, Deutche Telekom, France Telecom/Orange and Japanese NTT, and new global telecommunications operators such as WorldCom, Vodafone and Hutchison (D’Aveni, 2002; Heng & Low, 1990; Li & Whalley, 2002; Whalley, 2004). Many studies reported that the telecommunications service sector started to globalise (Ramamurti, 2000) following the earlier development of the telecommunications manufacturing sector, and this resulted in rapid consolidations of its players (Sirel & Wavermann, 2000). For example, Whalley (2004) predicted that in the mobile communications industry two types of operators would emerge: the global flag-ship operators such as Vodafone and Hutchison with global brands, many centralised operations and economies of scale advantages; and smaller regional operators. How have telcos from smaller countries been able to reposition themselves in this evolving industry value network and survived? Have they implemented niche strategies as suggested by some theories based on SMOPEC research (Benito et al. 2002; Dick and Merrett, 2007), or have they entered into strategic alliances as suggested by others (Merrett, 2002; Ramamurti & Sarathy, 1997); or have they been forced to withdraw from these types of very capital-intensive industries altogether (Morkel & Osegowitsch, 1999)? Another little researched area from the internationalisation process perspective is the development of joint-ventures (JVs) in the telecommunications industry. Studies have found that due to some remaining regulations in the industry, telcos in general have been forced to form JVs with local partners in many country markets (Granstrand, 1994). However, whether these types of entry modes have been utilized by SMOPEC telcos is still an under researched area. What impact these factors have had on the internationalisation strategies of SMOPEC telcos and their ability to identify/develop competitive advantages to overcome the smallness of their domestic markets, are also questions that this

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study is investigating. To illustrate process of internationalisation of telcos from SMOPECs, the findings from four case studies are discussed as follows.

CASE EXAMPLES ON THE INTERNATIONALISATION OF SMOPEC TELCOS The case companies used here to illustrate the internationalisation processes of telcos from SMOPECs and on the overall development of the industry value network, originate from three different continents: Sonera Oyj (Sonera) from Finland, Telia AB (publ) (Telia) from Sweden, Singapore Telecommunications Limited (SingTel) from Singapore, and Telstra Corporation Limited (Telstra) from Australia3. All of the aforementioned telcos were established in the early years of the industry, more than a century ago. For many decades they enjoyed protection from competition serving their home markets as national monopolies in most or all of their business areas. First international activities included co-operation with other national telcos from other countries. However, this was limited mostly to bilateral and multilateral interconnection negotiations and other friendly co-operation activities. The first phase of internationalisation with significant outward operations did not start until the 1970s and 1980s. However, when this occured their internationalisation patterns deviated from those predicted by traditional theories, especially with regards to market strategies. The first international operations were management contracts and consulting projects, but not in countries within a small psychic distance, but in developing countries, often even outside their home continents. For instance, Finnish Sonera established operations in Africa and South East Asia; Swedish Telia in Africa and Asia; Singaporean SingTel in the Middle East and some developing

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

African and Asian countries, and Australian Telstra in the Middle East and developing Asian countries. That is, mainly target markets with long cultural, economic and/or geographical distance from home markets4. Interestingly, the case companies adapted their product strategies. Instead of trying to enter international markets with their asset-based/location-bound services, as predicted by research findings on these types of service companies, they operated through consulting-projects and management contracts by ‘exporting’ their personnel. In this regard their product and operation strategies followed the incremental patterns that the traditional process theories for manufacturing companies suggested. This was against general predictions of an early entry mode in an asset-based-location-based service industry. In the second phase, in the 1990s, the case study companies entered international markets with more committed operation modes, such as JVs and, in some rare cases, in full-ownership modes. It can be argued that during this phase the target market selections and product strategies were very opportunistic with no clear patterns. For example, Telstra acquired interests in an Indonesian fixed-line business, and also had some operations in India and Vietnam, but they also established a full-service subsidiary in New Zealand. Soon they also acquired full ownership of a mobile operator in Hong Kong. Telia invested in mobile and fixed-line operators in the Baltic countries (Estonia, Latvia, Lithuania), and in many Latin American and African countries, but also established/acquired subsidiaries in Denmark and Finland. Sonera invested in JVs in both mobile and fixed-line operators in the Baltic countries, and in datacom and mobile operations in Russia. In addition it invested in mobile operators in Hong Kong, Hungary, Lebanon and Turkey. SingTel acquired shares in a full-service operator in Philippines, mobile operators in Belgium and Norway, and in cable-TV operators in Sweden and the U.K. Soon they also entered into equity

partnerships with mobile operators in Thailand and India. With regard to their market strategies the case companies’ internationalisation patterns varied significantly from those suggested by traditional internationalisation process theories. Most entries of the case companies were not to neighbouring developed countries with small psychic distance, but to culturally very different, economically less developed and, in many cases, also geographically distant countries. It could be argued that in both phase one and two the market strategies were very opportunistic, based on the need to achieve first mover advantages in an industry with network externalities, oligopolistic structure and the overall competitive situation. What contributed to the deviations in the market strategies of the case companies was that they had a competitive advantage in target countries due to their technical and marketing knowledge, but this advantage applied mostly in developing markets, rather that in other developed markets. However, the high capital intensity and host government regulations also created some limitations. As discussed, some of these challenges may have been significant especially for telcos from SMOPECs. This was reported to be one reason why the case companies were willing to remain as minority shareholders in many of their international JVs, a position that many of the more dominant industry operators seemed to try to avoid and overcome. It must also be noted, though, that at the end of phase two the case companies also had implemented some relatively aggressive and significant entries to some large and developed countries, such as SingTel’s acquisition of Optus in Australia, Sonera’s acquisitions of a minority share of a US-based mobile operator and an expensive 3G-license in Germany, and the significant investments by Telia, Telstra and SingTel in large regional data networks. This was partly caused by the ‘follow the herd’ phenomen in this oligopolistic industry, further intensified by domestic push forces and

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pressures to grow mainly, but not exclusively from the financial markets. In addition, during this high growth phase in the industry some of the case companies established specialised subsidiaries with objectives to achieve a global market leadership in their own niche businesses, such as Sonera’s Zed and Telia’s Speedy Tomato in the mobile portal business, and Sonera’s Smart Trust in the mobile payment sector. It can be further argued that at some level they tried to follow similar strategies to born global companies. However, these operations were not very successful and most of them have either been divested or terminated. While these events can be partly attributed to changes in market sentiment, difficulties in trying to combine very different organisation and market strategies within one group of companies was also an important factor. In other words, the parent companies followed multinational organisation strategies in which units in very different host countries were operating relatively independently, whereas the ‘born global’ companies tried to follow more global organisation structures. Further, it seemed that within an oligopolistic industry in which competition among telcos intensified after borders had opened, other telcos were reluctant to buy content from their potential competitors’ subsidiaries. Clearly the search for new positons in the evolving value network was a great challenge for the case companies. By the end of 2000 and early 2001, the general market sentiment deteriorated significantly. This resulted in changes in the internationalisation of the case companies. Thus, the third phase of their internationalisation was in clear contrast to the aggressive and opportunistic strategies in phases one and two. In many areas the processes were reversed, as the case companies started to focus on their core competences and on markets close to home, resulting in divestments of several of their earlier investments. Most new investments in distant markets were frozen. These de-internationalisation developments were different from

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the more deterministic and linear processes that most traditional process models suggested5. With regard to market strategies the focus was now on the home continent, or even the more narrowly defined home region, such as Northern Europe for Telia. The era of globalisation was over, at least for now, and the case companies became regional. Also, their product strategies became more focused; for example, on mobile communications in some new high growth markets, although the case companies still remained as integrated full-service operators in their home and close neighbouring markets, rather than becomng pure niche companies with a focus on just one business area. In the last phase, starting in 2002/2003, the case companies started to slowly look for new growth opportunities, but this time growth was focused mostly on new investments in their own region, in neighbouring countries, and to increase their ownership shares in their existing investments. It can be argued that their organisation structures developed from multinational to more transnational ones. They started to look for and gain synergies across their regional country organisations. This became possible as differences between different country organisations declined and operational and managerial control became easier due to increased ownership shares. Moreover, the overall internationalisation patterns became more gradual, and closer to the patterns suggested by traditional process theories. Examples of this phase were Telia’s and Sonera’s merger to form a multi-country telco in Northern Europe, and SingTel’s closer integration of many of its activities with its largest subsidiary, Optus in Australia, and also closer integration between its’ other regional JVs. However, in spite of this closer integration, the individual country organisations of each case company maintained their domestic company names and brands; that is, in many areas multinational strategies prevailed, instead of them moving towards more integrated and global-type of strategies.

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

It is also notable that throughout the four phases of internationalisation discussed previously, in their business-to-business (B2B) operations the case companies followed internationalisation patterns comparable to the ones reported in earlier studies of B2B-services (Aharoni, 2000; Roberts, 1998). That is, they established offices in other developed countries, in neighbouring countries with both small cultural and geographical distance, but especially in the leading markets in their continent and/or around the world. For instance, they established offices in London and other large cities in Europe, SingTel in most major Asian business cities, and Telstra in many of them, and all of them also had offices in the U.S. In addition, they joined in alliances with other telcos to be able to provide even more comprehensive global services to their global MNC-customers. The process, with regard to operation strategies, was relatively rapid. This is common among business services with follow-the customer strategies, as uncertainties and risks to internationalisation are rather low. This is both because of the relatively small size of the offices and, as for the case companies, the first entries were made to serve their domestic industrialised customers who had internationalised earlier. On the other hand, with regard to market strategies, the B2B-activities followed much more traditional patterns, also supporting earlier theories on B2B-services. It must be noted, though, that for SMOPEC telcos there are relatively fewer MNCs to follow, as the head quarters of most of the largest MNCs in the world originate in the largest economies rather than in SMOPECs. Thus, it could be argued that the importance of international B2B customers has been smaller for SMOPEC telcos than for the most globalised large country-originated telcos. So far the share of the revenues for the case companies from their international B2B operations have been moderate when compared to their B2C and domestic B2B operations6. When analysing factors that have contributed to these developments, it can be seen that industry

specific factors such as deregulation/regulation developments, the oligopolistic nature of the industry (limiting opportunities in each country market), economies of scale advantages7, technological developments, the growth pace of the industry, and the nature of the products (i.e. asset-specific/capital-intensive services consisting of complex systems and physical networks), have caused their internationalisation strategies to be rapid and irregular. This supports the findings of Sarkar et al. (1999) discussed earlier. Rapid industry growth together with limited opportunities created high real and perceived ‘first mover advantages’. Thus telcos sought country markets with limited barriers to entry almost independent of their geographical location. These results also support Ramamurti’s (2000) findings of ‘first mover advantage’ in the industry, and Stientra et al.’s (2004) findings of ‘herd-behaviour’ mentioned earlier. However, the high initial capital investments that were required in telecommuinications networks created additional challenges to the case study companies, as was predicted. With their limited resources and due to the relatively high risks involved, they were not able to enter large markets rapidly, at least not several large markets simultaneously. This varied from the strategies of the largest national telcos in the industry and of the more specialised companies such as Vodafone in mobile communications and Equant in data communications. For SMOPEC telcos entries to large developed markets seemed to be rare exceptions, and most of these few entries resulted in de-internationalisation and/or divestment decisions at a later phase of the process. Operation strategies of the case companies were based mostly on committed operation modes, as expected in network industries, but there was also interesting evidence of adaptations in their product strategies to make it possible to use less committed operation modes in the early phases of the internationalisation process. This strategy followed more of the processes suggested

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by the traditional intenationalistaion theories on manufacturing companies or hard-services, a finding that could provide an example of an alternative early phase entry strategy for a telco from a smaller country, when compared to more aggressive international entries by larger service MNCs in these types of industries. Also, the use of strategic alliances and JVs was common, following the expectations for a SMOPEC telco in a capital-intensive industry. However, it needs to be emphasized that the role of non-equity alliances diminished significantly over the process of internationalisation. It seems that even for telcos from SMOPECs the challenges of entering and maintaining an alliance with another telco in a situation in which competition is rapidly globalising, became greater than the possible benefits and synergies from the alliance. On the other hand, throughout the process JVs have been the most common international operation mode for the case companies. Unlike many large telcos, the case companies seemed to be relatively compliant as minority owners in many of these JVs. All of them emphasized the importance of owning a significant share of a JV and being the largest telco owner, but in many cases the ownership shares of 20 - 40 % were perceived to be sufficient. It could be argued that this willingness to work together with local partners, instead of aiming actively for a dominant role may have contributed to the attractiveness of these companies as JV partners. This difference in approaches may also relate to differences in their organisation strategies: for a global company the dominant position is important in order to gain control of the operations and to align them with a more centralised model. This was rarely a requirement from the SMOPEC telcos. In addition, as the telco sector is often perceived to be very strategic for a country and governments play an important role, political strategies are often a very important factor in the JV negotiations. In this type of environment SMOPEC telcos were often perceived to be less threatening and the

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power balance to be more even with local partners than would be the case with telcos from the largest economies in the world. It could be argued then, that this can be a competitive advantage for SMOPEC telcos when entering foreign markets, especially in many developing countries. With regard to their product strategies, the case companies tried to implement global niche strategies, but unlike for many SMOPEC firms, these were not found to be a successful way to internationalise. It could be argued that these strategies did not fit well with the overall strategies of the case companies. It can be argued that telcos have followed a different path in their internationalisation than, for example, large manufacturing companies or ‘born globals’. This supports the earlier studies of Sarkar et al. (1999) and Stientstra et al. (2004). In addition, several features were emphasized by telcos from SMOPECs: adjustments in product strategies at the early phase of their internationalisation, emphasis on distant developing markets in their market strategies, emphasis on minority JVs, and all implemented multinational organisation strategies (e.g. no global brands) with some later transnational characteristics. A further interesting finding was a possible competitive advantage arising from the SMOPEC telcos being perceived as less threatening by the host governments and potential host country JV-partners than similar companies from large, developed countries. All this may have contributed to the belief that SMOPEC telcos have not implemented global organisation strategies. It could equally be argued that when moving onwards from multinational structures/strategies, a transnational organisation strategy is more feasible for SMOPEC telcos than a global strategy; given that, the role of the domestic market is perceived as less important and dominant for the whole company8. As such, this may create a situation in which it is relatively easier/more natural for a SMOPEC telco to allow its country organisations to participate in the decision making and development processes of the

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

whole company. Some early findings of this type of behaviour were observed in our cases, although this issue requires furter investigation9. Furthermore, the findings reveal that there have been four separate phases in which the case companies have internationalised: Learning Phase, Opportunistic Phase, De-internationalisation Phase, and Maturisation Phase (Laanti, 2008). This is demonstrated in Figure 3. This identification of separate phases in the process is different from most traditional and deterministic theories, and also adds to the existing research on services. It could be argued that the growth pace of the industry combined with some pressures from the financial markets have been significant factors contributing to these phases. During the early phases ‘herd-behaviour’ was relatively strong, whereas during the later phases more strategic differentiation occurred, which supports the integration of strategic management concepts to the conceptual frameworks analysing internationalisation processes of the firm. This also supports the findings of Stienstra et al. (2004), discussed earlier, but overall this is a topic that requires further research. Although the first two phases included some global aspirations and strategies, and attempts to implement global focused niche-based product strategies with some of their operations, the case companies have recently implemented much more

regional strategies. They have remained mostly regional players with integrated product strategies benefiting from economies of scope advantages when providing fixed, mobile and data services, especially in their domestic markets, and they have also remained vertically integrated with regards to their network ownership and service operations (rather than becoming virtual network operators). It needs to be noted that some researchers have argued that even the most globalised telcos, such as Vodafone and Hutchison, still generate a large part of their revenues from one continent (Rugman, 2003), and also seem to follow multinational strategies in some of their operations, such as network purchases (Whalley, 2004). That is, although there are differences in this perspective between telcos from SMOPECs and the largest and most ‘global’ telcos in the industry, all telcos still fall behind in globalisation developments when compared to most other companies in the industry value network. These observations support the findings of Proff (2002) and Rugman (2003) that inspite of general development from domestic to more international markets, many industries are still regional rather than global. At one extreme are global manufacturers such as Nokia and Ericsson (Rugman, 2003; Steinbock, 2003), and born global companies such as many global softaware companies (Bell, 1995). At the other end are many retailing companies, which

Figure 3. Phases in telco internationalisation (adapted from Laanti et al (2006))

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Evolving Value Networks and Internationalisation of National Telecommuncation Companies

have started to internationalise, but are still more or content aggregation strategies, have not been regional rather than global in their nature (Rugman very successful. It remains to be seen how this & Girod, 2003). Pure B2B services seem to follow situation will develop in the future. the traditional process in their internationalisation, but they often do this more rapidly and end up to be ‘global’ companies (Roberts, 1999). CONCLUSION AND FUTURE In Figure 4 (Global Industry Value Network) RESEARCH OPPORTUNITIES these different approaches to global and regional strategies between different companies within Telcos’ share of the domestic value chain has the telecommunications industry, and the vertical decreased significantly as new players have integration/disintegration within and across the entered their2003; domestic markets global manufacturers such as Nokia and Ericsson (Rugman, Steinbock, 2003),and andvalue born chains companies such as manystrategic global softaware companies (Bell, 1995). the other end are On the value chains,global are illustrated. Different have disintegrated intoAtvalue systems. manyare retailing companies, which have internationalise, but are still has morealso regional options for telcos highlighted in the right sidestarted toother hand, convergence opened new rather than global in their nature (Rugman & Girod, 2003). Pure B2B services seem to follow of the figure:theglobal network operators, global opportunities in new business sectors, traditional process in their internationalisation, but they often do this more rapidly and endboth in service providers, network (Roberts, operators up to beregional ‘global’ companies 1999). domestic and internatonal markets. Together and regional service providers. As discussed, this more intensive competition domestically, In Figure 4 (Global Industry Network) these different approaches to global and these developments seem to indicate thatValue although and these new opportunities have forced telcos regional strategies between different companies within the telecommunications industry, and some of the largest telcos have been implementing enterthe international the vertical integration/disintegration within andtoacross value chains,markets. are illustrated. global strategies at some level, telcos from SMODifferent strategic options for telcos are highlightedBased in the on right of the results figure: global theside research on value networks service providers, regional operators and regional service PECs follow network mostly operators, regional global network operator in thenetwork telecommunications industry, earlier reproviders. As discussed, these developments seem to indicate that although some of the strategies. Some early tries to implement global search on telco internationalisation, and this study largest telcos have been implementing global strategies at some level, telcos from SMOPECs service provider (niche) strategies or to diversify on the internationalisation of SMOPEC telcos, it follow mostly regional network operator strategies. Some early tries to implement global service (niche) startegies or to diversify their operations to global application their operations to provider global application software can be argued that telcos have followed different software or content aggregation strategies, have not been very successful. It remains to be seen how this situation will develop in the future.

Figure 4. Global valuevalue network figure industry 4: Global Industry network Global Network Operators?

Global Service Operators?

Regional Network Operators?

Global Players

Network Operators

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Content Aggregation

Application Software

Network Operators

Platforms

Equipment Manufacturers

Contract Manufacturers

Global Reach

Network Operators

Regional Service Operators?

Network Operators

Service Operators

Network Operators

Service Operators

Network Operators

Service Operators

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

internationalisation strategies to telecommunications equipment manufacturers or ‘born globals’ in the industry. The reasons for this can be found in their different business logic and in the characteristics of the sector, resulting in exposure to different types of challenges when compared to the manufacturing sector or ‘born globals’. For example, deregulation/regulation, the greater role of governments, network externalities, the different nature of economies of scale advantages, and the high capital intensity of the sector create unique challenges for telcos. All this has resulted in a unique competitive environment, with some oligopolistic structures. In addition, it was illustrated that telcos from SMOPECs face their own specific challenges, resulting in alternative patterns of internationalisation, but they have been able to develop some useful competitive advantages against their larger competitors. It is evident that the development of value networks in the telecommunications industry or the ICT-industry is still ongoing. Interesting questions remain with regard to telcos’ internationalisation in the future: what will be the successful strategies, business models, and optimal positions within the industry value network for telcos more generally, and for telcos from SMOPECs particularly? These questions will provide some future research avenues. First, more empirical and longitudinal studies are required to analyse market strategies of telcos, that is, horizontal (geographical) integration in the value network. These studies could analyse if regionalisation developments are just another phase in the process and if global strategies will prevail in the future. Second, this question leads to a related research topic. As mentioned, the different development levels between different country markets caused organisation strategies of most telcos (and all SMOPEC telcos) to be multinational rather than global. However, it would be interesting to investigate how the situation changes when the industry matures further and the development levels between country markets is closer than at

present. That is, would this result in more consolidations of telcos across national borders and more integrated organisation strategies? Third, the value chain and value network concepts have been useful to analyse operation strategies of telcos, especially their vertical integration vs. disintegration along the value chain. Now some network independent service providers have emerged in markets, but so far they have not been able to succeed against more integrated traditional telcos. More longitudinal studies on this issue are required. Fourth, with regards to their product strategies most telcos still seem to follow mostly horizontally integrated product strategies, especially SMOPEC telcos in their domestic markets. By doing this they resemble many large retail companies in their business logic. That is, they sell and package services developed by their international suppliers, and utilise economies of scope advantages. Future studies could analyse if these are the winning strategies in the future or will more focussed product strategies become more successful, as they may allow more opportunities to specialise and internationalise, even for companies with limited resources. Naturally, one of the most relevant and important questions for SMOPEC telcos is whether they are able to survive as independent organisations or will the long predicted consolidation developments eventually result in a few large telcos dominating the sector. These and other questions with regards to optimal positioning in the globalising ICT industry seem to remain relevant to researchers, managers of internationalising telcos, to other industry players, and to policy makers. In investigating these questions the concept of value network and the internationalisation process models can provide a useful analytical framework.

ACKNOWLEDGMENTS The authors want to acknowledge the key interviewees of each case company for their valuable 187

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support for the project. The authors want also to thank the following organisations for providing funding and support to the project: The Foundation for Economic Education, The Finnish Cultural Foundation, HPY Research Foundation, and International Telecommunication Union (ITU). The early version of this paper has been presented in ITU 2006 Telecom World Conference (4th- 8th December) in Hong Kong. The authors have a permission from International Telecommunications Union to publish the developed version also as a book chapter.

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KEY TERMS* Globalisation: The OECD (2007) defined globalisation from an economic perspective: “The term globalisation is generally used to describe an increasing internationalisation of markets for goods and services, the means of production, financial systems, competition, corporations, technology and industries”. Whereas Clark and Knowles (2003) included a broader view in their definition: “The process by which economic, political, cultural, social, and other relevant systems of nations are integrating into World Systems is called globalisation.” It seems that when analysing the internationalisation of many service companies, especially in network industries such as the telecommunications industry, it is necessary to include this broader perspective of globalisation into the conceptual framework, as often political and cultural systems play a significant role in the internationalisation of services. ICT Industry: The convergence of the telecommunications industry with the computing and broadcasting industries resulted in a broader definition of Information and Communications Technologies (ICT). As defined by OECD: “… ICT sector refers to equipment and services related to broadcasting, computing and telecommunications, all of which capture and display information electronically.” (in UN Social Economic Council’s Report of the International Telecommunication

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Union on information and communication technologies statistics, 2004). Internationalisation Process: describes a dynamic process of a firm’s entry to international markets. In most cases the longitudinal studies of international processes include analyses of firms’ operation modes and market strategies. Most of the traditional internationalisation process models have emphasized the gradual and incremental nature of the firm’s internationalisation (see e.g. Bilkey & Tesar, 1977; Cavusgil, 1984; Johanson & Vahlne, 1977; Johanson & Wiedersheim-Paul, 1975; Luostarinen, 1979, 1994). Small and Open Economies (SMOPECs): Small and open economies include countries such as Austria, Denmark, Finland, Ireland, New Zealand, Portugal, Norway, Sweden, and Switzerland, who have integrated themselves with the world economy by lowering or eliminating their trade barriers (Benito et al., 2002; Kirpalani & Luostarinen, 1999; Maitland & Nicholas, 2002; Merrett, 2002). The broader definition includes also medium-size countries such as Australia and newly industrialised countries such as Hong Kong (Maitland & Nicholas, 2002). Although Australia is already a medium-sized country with regards to its population, its companies face similar challenges in their internationalisation than companies from other SMOPECs (Dick & Merrett, 2007; Liesch et al., 2002). Telcos: Telco is the term for a telecommunication operator; that is, a company that provides telecommunications services such as fixed-line, mobile and data services for end-customers. Most of the traditional telcos have been government owned telecommunication companies and usually also national monopolies, or at least duopolies. Telecommunications Industry: Consisted traditionally of the manufacturers and network operators in fixed, mobile and data communications businesses. More recently many other companies, such as contract manufacturers, service provid-

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ers, and application and content providers have emerged to be important players in the industry (see also the definition of the ICT industry). Value Chain: The concept of value chain has been widely covered in the strategic management literature, most notably by Porter (1985). A value chain arises from a company’s activities and internal business processes to create value for its customers (Porter, 1985). This value chain of a company then belongs to an industry value chain or system (Porter, 1985). Value Networks: The difference in the definition of value networks, when compared to the traditional definition of value chains, is that in a value network there are several entry and exit points, and that activities take place simultaneously instead of successively (Li & Whalley, 2002).

Endnotes

*

1



2



3



Most of these definitions are used also in the wider study on the internationalisation of telcos that this paper is based on (Laanti, 2008). It must be noted, though, that in some countries the telecom equipment manufacturers have been independent actors also historically, although often very closely linked with national telcos. Telecommunications equipment manufacturers were actually the first companies in the industry who started to internationalise rapidly. These case data were collected as a part of a broader cross-border multi-case study of the internationalisation of SMOPEC telcos that was mentioned earlier (Laanti, 2008). Australia and small and newly industrialised Asian countries were included as SMOPECs, based on suggestions by Maitland and

Evolving Value Networks and Internationalisation of National Telecommuncation Companies

4



5





6

Nicholas (2002). While it is acknowledged here that Australia is a medium-sized country with regards to its population size, its companies nevertheless face similar challenges in their internationalisation as companies from other SMOPECs (Dick & Merrett, 2007; Liesch et al., 2002). It must be noted that many of these projects were based on governments’ foreign aid to developing countries. Thus, the risks and uncertainties for the telcos were relatively limited. This issue seem to further emphasize the important role of governments in the internationalisation processes of telcos. Note that some studies on internationalisation processes have also reported remarkable de-internationalisation activities (e.g. Welch & Benito, 1996). Due the position of Singapore as a regional hub for many global MNCs SingTel seems to have had a better position compared to

7



8





9

other SMOPEC telcos to target international B2B customers and it seems that it has been relatively successful in this perspective, at least at the regional level. Instead of global scale of advantages, in network industries the most scale advantages occur at local or regional level. For instance, SingTel’s domestic operations are much smaller than their Australian operations. Some evidence of successful transnational organisation strategies were observed in some of the case companies, such as the internationally diversified compositions of the board of directors and management teams; and the active search and import of ideas between different country organisations as well as from other country organisations back to the home country - a key characteristic of a transnational organisation.

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Chapter XII

The Effect of Non-Market Strategies in the Mobile Industry Zulima Fernández Universidad Carlos III de Madrid, Spain Belén Usero Sánchez Universidad Carlos III de Madrid, Spain

Abstract This chapter analyzes the role of non-market actions (NMAs) in the competitive position of firms in the European mobile telecommunications industry. First, the bases and uses of NMAs are reviewed and classified. Second, the use of legal actions as NMAs to erode the competitive position of first-mover firms is examined. Third, the findings of an empirical study confirming the effectiveness of legal actions as competition tools in the European mobile telecommunications industry are analyzed. Lastly, some conclusions, future lines of research and practical recommendations are presented

INTRODUCTION Over the last decade the European mobile telecommunications industry has experienced unprecedented growth. The industry has expanded from a mere 35 million users with an average penetration rate of 12 percent in 1996 to more than 450 million users with an average penetration rate of over 100 percent at the end of 2006. In fact, 17 European Union (EU) member states

have now exceeded 100 percent penetration (European Union, 2007). The spread of digital technologies and market liberalization is responsible for this rapid expansion. Not all operators, however, have benefited equally. The technology in the mobile telecommunications industry is available to all firms, and identifying and copying innovations introduced by competitors is easy. Although this situation should cause pioneer operators to lose their first-mover

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The Effect of Non-Market Strategies in the Mobile Industry

advantage rapidly, pioneers have been shown to maintain their advantage (Fernández and Usero, 2007). An analysis of other—presumably more effective—ways of competing for follower firms, then, is needed. Firms can defend themselves against rivals with a variety of competitive actions such as product, pricing or advertising activities (Smith et al., 1992). These are all market actions, but non-market actions (NMAs) are available to firms too. NMAs target politicians and regulators, the media, citizens and courts. Lobbying government, managing public or stakeholder opinion, and taking legal actions against competitors or the government itself are all examples. The use of NMAs–particularly legal actions–to obtain competitive advantages has become “a necessity, not an option, in business” (Shell, 2004: 19). NMAs serve to complement–even replace–more conventional actions that are designed to implement a firm’s strategy (Yoffie and Bergenstein, 1985). Their use is especially effective when business models and technologies can be easily replicated or when many of the business opportunities are controlled by government (Baron, 1995), as is the case in the mobile telecommunications industry. Evaluating the effectiveness of NMAs to erode pioneer advantage in this industry, then, is a topic that merits discussion. Legal actions such as filing lawsuits and making complaints to regulatory bodies are among the most typically used NMAs. It is, for example, common for operators without significant market power to complain to regulatory agencies about high interconnection charges or difficulties to install antennas, while dominant operators complain about the help they are required to provide other firms. Despite this, however, few empirical works rigorously study the impact of this type of NMA. Consequently, this chapter has two objectives:

1.

2.

To discuss the bases and uses of NMAs and highlight the main types employed in the mobile telecommunications industry. To analyze the use of legal actions to erode the competitive position of first-mover firms in the mobile telecommunications industry.

The chapter is organized as follows. First, the European mobile telecommunications industry is briefly described. Second, the effectiveness of NMAs as competition tools and their relevance to the mobile telecommunications industry are discussed. Third, the different types of advantages that legal actions bring are analyzed, along with the findings of an empirical study confirming the effectiveness of legal actions at eroding the pioneer advantage of European operators. The chapter concludes with some final thoughts and outlines some possible future lines of research.

THE EUROPEAN MOBILE TELECOMMUNICATIONS INDUSTRY One of the reasons the mobile telecommunications industry has grown rapidly in Europe is the strong support given to it by the European Union (EU). The EU has made great efforts to establish a harmonized framework for the regulation of electronic communications services and networks, and associated facilities and services. The process began with the Green Paper on Mobile and Personal Communications (COM(94)145 final) and finished with Directive 2002/21/EC and another four specific Directives on a common regulatory framework for electronic communications networks and services. This growth of the European market can be clearly traced through three stages that correspond to the technology used (Figure 1). In the 1980s almost all monopolies operating in the fixed telecommunications industry obtained the sole license to operate with analog technology. The United Kingdom and Sweden had a duopoly from

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The Effect of Non-Market Strategies in the Mobile Industry

Figure 1. The evolution of mobile telecommunications systems 1st G ener ation (A nalog system) 1980s Monopoly –except UK , Sweden and France

2nd G ener ation (Digital system: G SM 900, DC S 1800) 1993-

3r d G ener ation (Digital system: UM T S) 2001-

Monopoly and competition

Competition

the beginning, with France reaching a similar state four years later. In the 1990s the introduction of digital technology (GSM-900, DCS-1800) made it possible to establish a European standardization system based on GSM technology. The resulting trans-European network overcame the problems of incompatibility that had existed with the analog systems. In addition, all countries opened their domestic markets to competition. The process, though, was not similar in all cases. In Sweden, Germany, Denmark and Portugal two or three licenses were granted from the beginning, eliminating the monopoly that had existed with analog technology. In Switzerland and Luxembourg, however, it took more than four years for the regulatory authorities to grant a second license. The licensing of third generation (UMTS) systems began in Europe in 2000. In countries like Spain and Sweden, the competitive tendering model was employed to encourage rapid deployment. In the UK, however, the government opted for a public tendering model. The huge revenue the UK government raised in this way encouraged many other European countries to adopt the same system, with the result that many firms have had their level of competitiveness damaged by the inflated prices they paid for UMTS licenses. Currently, the degree of UMTS implementation is still at a very embryonic phase. At present, there are 68 network operators in the EU, Norway and Switzerland offering digital mobile telephony services (GSM and, in most cases, UMTS) (see Appendix 1).

196

NON-MARKET ACTIONS AS COMPETITION TOOLS Firms operate in both market and non-market environments. In market environments they relate to their competitors, suppliers and customers by undertaking actions such as launching new products, increasing capacity, cutting prices or running promotions. The non-market environment includes the interactions between the firm and other parties such as the public, the media and public institutions (Baron, 1995). The activity of the firm is limited by government regulation, while it is also often influenced by the media or the opinions and desires of stakeholders (e.g., employees or customers, among others). This is why firms attempt to influence norms, regulations and public policies in ways that favor their interests and–if possible–harm those of their competitors (Capron and Chatain, 2008). Similarly, firms take actions to shape public or stakeholder opinion. In short, non-market actions (NMAs) such as litigation, testifying at government hearings, lobbying, advocacy advertising, or constituency building are tools that firms can use to support their strategies. NMAs complement–sometimes even replace–market actions taken to build competitive advantages; firms use them to attack or protect themselves from competitors. As with market actions, firms seek to shape or restructure the environment so that it is more favorable for their interests. NMAs may bring individual advantages for the undertaking firm (e.g., information not

The Effect of Non-Market Strategies in the Mobile Industry

Figure 2. Relationship between market and non-market environments Market environment determines importance of non-

MA R K E T

(competitors, suppliers, customers)

Market actions

Non-market actions

FIR M

NON-MA R K E T

(laws, regulations, public policy, public opinion)

Non-market environment shapes business opportunities in the market place

available to rivals) or advantages for the industry as a whole (e.g., adding trade barriers). Non-market environments, then, shape the competition in the market, while firms’ market actions modify non-market issues. In other words, both environments are inter-related (see Figure 2).

Firms may employ many types of NMA, each one with a specific objective and targeting a specific agent. Table 1 classifies the most important and common NMAs in the literature. Various types of actions are identified: information, financial contributions, constituency building and legal.

Table 1. Types of non-market actions (source: Adapted from Baron (1993) and Hillman and Hitt (1999)) TYPES OF NON-MARKET ACTION

DEFINITION

Information

Provide information to public decision makers, including measures such as: 1) Lobbying regulators, civil servants and politicians to influence their decisions. 2) Reporting research and survey results. 3) Testifying as experts in hearings or before other government bodies. 4) Supplying public decision makers with position papers or technical reports.

Financial contributions

Provide financial support, including measures such as: 1) Making financial contributions to politicians or to political parties. 2) Hiring personnel with political experience.

Constituency building

Seeks to gain voter, citizen and activist support or interest, including measures such as: 1) Grassroots mobilization of employees, suppliers or others linked to the firm. 2) Advocacy advertising, when a particular position is advertised to the public.

Legal

Formal complaints concerning allegedly infringed rights or dissatisfaction with the existing legislation, including measures such as: 1) Filing lawsuits against rivals or regulatory authorities. 2) Regulatory petitions.

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The Effect of Non-Market Strategies in the Mobile Industry

Information actions and financial contributions are two types of NMA that give access to politicians and regulators (Schuler et al., 2002). Information actions seek to influence politicians and regulators by providing them with specific information about policy preferences or the consequences of decisions. Lobbying is the best known example. Firms also work with regulators by producing technical reports to advise the relevant authorities and by sending managers and technical experts to declare before them. In addition to this, firms try to access the policy-making process or exert influence over regulatory bodies by offering financial incentives to decision makers, or to the parties or institutions they belong to (Hillman and Hitt, 1999). Likewise, constituency building encourages groups with similar interests to those of the firm to actively defend the firm’s interests. Firms address different constituencies in order to encourage a particular behavior or position. Firms using NMAs have focused on public institutions such as legislators and regulatory agencies. Nevertheless, private interest groups (e.g., non-governmental organizations (NGOs) and activists) that attempt to influence the industry via the media and com-

munity mobilizations have now become the prime focus of these efforts. As a result, constituency building has become one of the most important NMAs used by firms. Lastly, firms file lawsuits against their competitors or the public administration. They take this action to protect their interests and rights; these legal actions seek to handicap competitors or gain direct advantages (Baron, 1995). Figure 3 shows the main relationships among the agents in non-market environments. NMAs are essential when opportunities are controlled by government (Baron, 1995), as well as when business models and technologies are easy to imitate. Because the mobile telecommunications industry has both characteristics (De Figueirido and Edwards, 2007), the use of various types of NMA is common. Table 2 details some examples of NMAs in this industry. Although the effects of these NMAs have not been examined in great detail, some studies have begun to measure their impact. Bonardi (1999) examines how in the early 1980s British Telecom used its close relationship with the UK government to hinder the deregulation process in the telecommunications industry. And De Figueirido

Figure 3. Non-market actions and non-market agents

POL I T I C I A NS, R E G UL A T OR S

  

Information Financial contributions L egal actions

 FIR MS

Constituency building C I T I Z E NS, ST A K E H OL DE R S



L egal actions C OUR T S

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The Effect of Non-Market Strategies in the Mobile Industry

Table 3. First-mover advantages in the mobile telecommunications industry NON-MARKET ACTION

EXAMPLE

Information

British Telecom tried to hinder deregulation of the British telecommunications industry (Bonardi, 1999)

Financial contributions

Private money in campaign contributions influences public policy outcomes (De Figueirido and Edwards, 2007)

Constituency building

Creation of a public opinion campaign designed to show that antennas posed no dangers to health

Legal

Telefónica Móviles España, S.A. embarked on legal actions against the Spanish regulatory authority (El País, 2006)

and Edwards (2007) look at how campaign contributions influence regulatory outcomes in the telecommunications industry. Specifically, they show how campaign contributions by incumbent firms and new entrants influence access prices for local loops of incumbents’ telephone networks. This analysis also suggests that the effects of campaign finance on regulatory outcomes can be rapid. Nonetheless, many other types of NMA exist that have not yet been studied. The next section focuses on one example–legal actions–that is particularly common in the mobile telecommunications industry.

THE EFFECT OF LITIGATION ON FIRST-MOVER ADVANTAGE IN THE MOBILE TELECOMMUNICATIONS INDUSTRY Three types of first-mover advantage exist (Lieberman and Montgomery, 1988): technological leadership, pre-emption of scarce resources, and the creation of buyer-switching costs. First,

technological leadership is gained by experience economies and R&D superiority. Second, pioneers can pre-empt scarce resources–such as favorable physical locations, inputs, plants and equipment or distribution and service systems–needed to develop the business. And lastly, switching costs serve to lock in customers. All these advantages make it more difficult for followers to compete with pioneers on a level playing field. As mobile telecommunications is an equipment-based service, the advantages for preemption are significant (Bharadwaj et al., 1993). For example, the location of base stations poses problems for firms that enter the market later as fewer sites are available and local residents usually oppose placing them in towns and cities. Pioneers can also take better advantage of experience economies because they have more time to accumulate production and lower unit costs, even though all operators–regardless of when they enter the market–have the same technology. Non-portability of numbers, network economies and subsidized phones are the most important switching cost in the mobile telecommunications industry. Non-portability keeps the customer captive due to the inconvenience of having to change telephone numbers when switching to another operator. A similar effect occurs with the high price operators charge clients who wish to terminate their contract but maintain their telephone number. As mobile networks are highly compatible, network economies are likely to result from price discrimination inside and outside the network. Lastly, operators offer customers discounts on new phones at the end of their contracts. This offer may be the most important captive reason now that the problem of portability has been resolved (see table 3). Some of these advantages are dependent on government and regulatory agencies. Time in monopoly has been shown to strengthen firstmover advantages (Fernández and Usero, 2007). It leads to an increase in customers, which favors the creation of network and scale economies and experience. Therefore, governments can reduce

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The Effect of Non-Market Strategies in the Mobile Industry

Table 3. First-mover advantages in the mobile telecommunications industry (source: Adapted from Fernández and Usero (2007)) PRIMARY SOURCES

FIRST-MOVER ADVANTAGES IN THE MOBILE INDUSTRY

Pre-emption

Location of base stations Scale economies

Technological leadership

Experience economies

Switching costs

Number portability Network economies Discounts on the purchase of phones

first-mover advantages by allowing new operators to enter the market as soon as possible. Regulatory agencies can also ease or tighten restrictions on the establishment of base stations, depending on the degree of resistance from the public. They also have the power to force pioneers to allow competitors to use their base stations, and to impose portability. Non-market actions (NMAs), then, are highly useful for pioneers as they can have an impact on government and regulators, and thus reinforce the first-mover advantage (Frynas et al., 2006). Followers use NMAs for similar reasons: to prevent pioneers from consolidating and improving their position. The main NMAs that followers have at their disposal are: providing public decision makers with information designed to encourage them to reconsider regulation, along with highlighting market power abuses by pioneers. These NMAs are undertaken by complaining to regulatory agencies, or as a last resort by taking the matter to court. Pioneers and followers in the mobile telecommunications industry, then, use legal actions as NMAs for a number of reasons. These include the detection of allegedly illegal behavior by competitors, the need to counteract the effects of regulation, keenness to hinder the entry of new competitors, and the intention to harm rivals.

200

1.

2.

3.

4.

Detecting allegedly illegal behavior by a competitor: Although government agencies are normally responsible for supervising competitive restrictive conducts, private parties–either customers or competitors–can detect this kind of behavior more easily and may bring lawsuits against other firms for monopolistic behavior. An example is provided by the obligation of pioneers to offer followers the use of their base stations for a limited period of time (Laffont et al., 1997). Incumbents, though, commonly restrain followers from using their stations, thus forcing followers to complain to the regulatory agencies and courts. Pioneers themselves, however, also complain about possible abuses by followers when using shared resources. Influencing regulation: Some operators in the mobile telecommunications industry have —significant market power—and work under more restrictive regulations than their competitors. These dominant operators, therefore, complain to the regulatory agencies and take legal actions to reduce the weight of regulation controlling interconnection prices and the rates competitors pay for the use of their installations or networks. In Spain, for example, Telefónica has filed more than 200 lawsuits against mobile interconnection charges, local loop unbundling, and universal service funding (El País, 2006). Hindering the entry or consolidation of new competitors: In order to exploit the first-mover advantage for a longer period of time, pioneers may file lawsuits against new entrants. Their intention is to make the case last as long as possible, thus discouraging the entry of further competitors, or at least preventing them from competing on equal terms (Shell and Yao, 2000). Harming rivals: The threat of legal actions distracts, delays, and imposes additional costs on rivals as the accused firm is forced

The Effect of Non-Market Strategies in the Mobile Industry



5.

to divert time and resources from more productive activities to defend itself from the lawsuit. Empirical research has found that markets react negatively to the news of legal action and punish the defendant, but not the plaintiff (Koku et al., 2001). Litigation between firms causes the defendant significant losses of wealth (Bhagat et al., 1998). Most of these losses can be ascribed to the possibility of restrictions being placed on competitive behavior rather than the threat of fines (Bizjak and Coles, 1995). Courts can be slow in reaching verdicts, so slow that decisions may even be handed down too late to help the plaintiff whose interests were abused by more powerful competitors. Litigation, though, can damage the defendant’s reputation (Field et al., 2005). A claim of abuse of market power may adversely affect the public image of a firm and hence its sales. Firms that violate regulations suffer reputation loss. Indeed, nearly all the defendant’s losses of wealth are caused by reputation loss rather than by penalties and litigation costs (Karpoff and Lott, 1999). Being criticized publicly by a competitor: Firms sometimes make public–and baseless–attacks on their rivals, causing the accused firm to sue its competitors for damages.

In short, the evidence seems to point to pioneers and followers using legal actions to improve their competitive position. To test this hypothesis the authors studied the European mobile telecommunications industry with a database containing information on legal actions undertaken by pioneer and follower mobile phone firms from 1997 to 2000. The sample begins in 1997 because at that time there were at least two firms competing in the digital technology market in all of the countries. This makes it possible to study a group of pioneer firms as well as followers. The cut-off point was

2000 because in 2001 third generation (UMTS) licenses began to be granted. The data on operators’ legal actions were obtained by electronically searching the main general and business newspapers in the countries where they were working, along with several European trade journals from the telecommunications industry–all included in the Reuters database. Structured content analysis (Jauch et al., 1980) was used to identify the legal actions of all the firms under study. The steps followed in the collection and sorting of news items are described in Appendix B (Usero and Fernández, 2005). The result of this meticulous analysis of news items was the identification of 109 legal actions performed by firms in the sample period (1997-2000). A preliminary descriptive analysis of the data reveals that pioneers and followers in the EU have similar litigious conduct. As regulation is often the source of first-mover advantages in this industry, it would seem logical for followers to use legal actions to counteract them. Nevertheless, followers do not litigate more than pioneers do. Even though the data in table 4 might seem to indicate that follower firms are more likely to undertake legal actions than pioneers, these differences–with the exception of the data for 1999–are not statistically significant. Both types of firms take a similar number of legal actions. Followers seek to diminish pioneers’ significant market power, and therefore constantly make demands to gain greater access to their rivals’ resources (base stations, customers, etc.), to reduce interconnection charges, and to allow mobile number portability. Meanwhile, pioneers bring lawsuits against both competitors and regulatory authorities to defend their advantages. A multiple regression analysis model was used to test whether the use of legal actions improves the competitive positions of pioneers and followers. The model includes two independent variables: pioneer legal actions in a particular country and year, and follower legal actions in a

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The Effect of Non-Market Strategies in the Mobile Industry

Table 4. Legal actions mean test Mean

Mean 1997

Mean 1998

Mean 1999

Mean 2000

Mean (Legal actionsFollowers) (Standard Deviation)

0.308 (0.568)

0.276 (0.527)

0.410 (0.594)

0.323 (0.584)

0.250 (0.556)

Mean (Legal actionsPioneers)

0.205 (0.502)

0.206 (0.491)

0.256 (0.548)

0.102 (0.306)

0.279 (0.619)

0.018

0.286

0.112

0.005

0.641

(Standard Deviation) p-value*

* P-values correspond to these mean tests: Mean (Legal actionsFollowers) - Mean (Legal actionsPioneers)) > 0

particular country and year. It also incorporates various control variables that may affect the erosion of pioneer advantage: months in monopoly, order of entry, market penetration and industry growth. The measurement of variables is included in Appendix C. The estimated model is of the form: Erosionijtp= β0 + β1* Pioneer legal activityitp + β2* Follower legal activityjtp + β3* Months in monopoly p + β4* Orderjp + β5*Penetrationtp + β6* Growthtp+β7*Market share of pioneeri(t-1)p + εijtp The analysis of longitudinal data with ordinary least squares is subject to violations of the conventional suppositions, mainly homocedasticity and auto-correlation. Not taking account of these problems may cause the estimations to be biased, resulting in an inflated statistical F value (Bergh and Holbein, 1997). Working with information on firms from different countries–as here–makes a problem of heterocedasticity highly likely. The Cook-Weisberg statistic indicated the presence of heterocedasticity when using models of ordinary least squares. The Wooldridge test confirmed the existence of an auto-correlation problem in the data. Crossed-sectional time-series linear models using feasible generalized least squares were used to get around both problems. After calculating the variance inflation factors (VIF) for all the variables, none of them was found to be higher than 2. This indicates that multicollinearity is not a problem in this study.

202

The results obtained for both pioneers and followers in the European mobile telecommunications industry (see table 5) show the effectiveness of legal actions for attacking rivals and improving competitive positions. The data show that pioneers that have filed more lawsuits succeeded in sustaining their competitive advantage–measured in terms of market share–for a longer period of time. The study also reveals, however, that the more litigious followers managed to erode pioneer advantage more intensely. Lastly, the results of the regression analysis confirm that the time in monopoly helps preserve the first-mover advantage. To sum up, this research confirms the effectiveness of legal actions in the fledgling European Table 5. Regression resultsa,b Model 1 Variable

β

Std. Dev.

Pioneer legal activity

0.094

0.025***

Follower legal activity

-0.038

0.019**

Months in monopoly

-0.004

0.001***

Order

0.158

0.035***

Penetration

0.001

0.001

Growth

0.002

0.001

Market share of pioneer “i”t-1

0.539

0.167***

Constant

-0.459

Log likelihood Χ2 (d,f,) a

57.50(7)***

N=183 in all models. *p y j ) I ( xi , y j ) =  , 0 otherwise

(2)

{x0, x1,..., xm – 1} is the set of different predicted values for churn customers, while {y0, y1,..., yn – 1} is the one of different predicted values for positive customers.

Principle 2: Mutual Information Between Variables should be Relatively Low Mutual information is a concept to measure how much information one variable tells about

385

Telecommunication Customer Detainment Management

another one. A higher mutual information between two variables means the two variables share more similar information. In this case, we can delete some redundant variables, to make sure the mutual information between variables is relatively low. Mutual information is computed by:

The former one reflects the amount of “disorder” of the target variable T, while the latter one reflects the amount of “disorder” of target variable T after considering a. Hence, mutual information is the amount of information that a provides to classify T.

III Variable Selection Process I(T, a) = H(T) – H(T / a)

(3)

Where: n

H (T ) = −∑ p (ai ) log p (ai )

(4)

i =1

Is the entropy of T m

H (T / a ) = −∑ j =1

n

∑ p(a b ) log p(a / b ) i =1

i

j

i

j

(5)

Is the conditional entropy of T, given the value of a;

Figure 4. Variable selection process

Modeling

Compute predictive ability of each variable

Select N variables with highest predictive capabilities

Compute mutual information of every two variables for the N variables

Select M variables based on the principle of low mutual information

Unsatisfied Validate selected variables Satisfied

Use selected variables train models

386

Variable selection process is shown in Figure 4: In practical applications, a variable is considered to be useful for churn prediction only when its AUC is larger than 0.5. In this way, the number of the variables can be determined. Two variables are kept only when the mutual information between the two variables is smaller than 0.5 and then the number of the variables used for building up prediction models can be determined. The variables selected can be used as inputs for initial churn prediction models. If the performances of the models are satisfying, the variables could be the final variables for prediction, otherwise future adjustment of the cutoff values of AUC and mutual information should be made to get better performances.

Customer churn prediction model is based on two basic assumptions: Assumption I. Different customer groups have different churn tendencies; Assumption II. Certain customers who churned from a company will have certain unusual consuming behaviors. Customer churn prediction model is eventually fitted into a churn probability function P(X), in which X stands for the eigenvector of customer (includes information stored in database which reflects the churn tendency, e.g. demographic information, account information and customer calling behavior). P(X) is defined within [0, 1]

Telecommunication Customer Detainment Management

and describes the customer churn rate if there is no detain measures for this customer in a certain coming period. Many methods are used for fitting P(X). The most common method is the multiple regressions, neural network, decision tree and the combination of these 3 methods. What needs to be mentioned is there is so few churned customers for a company that the ratio of regular customers to churned customers is high skew distribution in the whole sample. This point must be taken into fully consideration when modeling and feasible measures must be used.

within a certain range of customers (e.g. 10%) account for in all real churned customers. Lift value indicates the ratio of real churned customers within top n (n=10, 20…100) customers who has been sorted by churn possibility according to the prediction model to real churned customers within top n (n=10, 20…100) customers who has been sorted by churn possibility according to subjective judgment. That all aforementioned indicators are higher stands for a better model prediction performance.

Model Evaluation

Model Adjustment

Prediction and explanation are two main functions of churn prediction model. Issues of resource allocation, always somewhat thorny, still bring more challenges. Through prediction, the enterprise can focus on a small scale of customers (i.e. the most likely churners), and then pool resources to conduct customer detainment with pertinences. Through explanation, the enterprise can find some regular patterns of customers’ behavior, which will help the enterprise to better understand which factors have great impacts on customers’ loyalty and churn tendency. As for prediction, response rate, captured rate, lift value, ROC value and revenue curve are the common indexes to evaluate the prediction effect of the churn model. Response rate indicates that the percentage of churned customer in this situation:

If the model evaluation provides a satisfied result, there is no need adjusting the model and customer detainment strategy should be the next step; if not, the model should be adjusted or some other models should be selected.

Use churn prediction model to get the churn possibility of all customers; II. Sort all customers by churn possibility; III. Within a certain percentage of all customers (e.g. 10%), response rate stands for the percentage for which real churned customers account. I.

Captured response means the percentage that after sorting all customers by predicted churn possibility, how many real churned customers

Identification of Churn Customers Normally, the assertion for classification of customers is not provided by prediction models. Models return a probability from 0 to 1 to say customer belonged to a certain class rather than a Yes or No conclusion to answer whether customers will churn. Model users should take all constraints (e.g. different resources of the company) into consideration, set a threshold for churn probabilities accordingly and finally classify customers. A high probability stands for a high possibility it belongs to a class. So there should be a probability threshold p0, if p ≥ p0, this customer is identified as class A and vice versa. Before implementing the detainment strategy, customers should be identified for detainment according to the company’s practical situation, e.g. to classify into potential churned customer class. In this chapter, churn probability threshold is set by the maximum earning principle.

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Telecommunication Customer Detainment Management

Based on the aforementioned hypothesis, we could get Cost/Profit Matrix as seen in Table 2:

Table 1. Model prediction matrix Real churned

Regular

Predicted churned

N11(p0)

N10(p0)

Predicted regular

N01(p0)

N00(p0)

Identification of Churned Customer Group Based on Model Prediction Matrix and Cost/Profit Matrix, total profit for detainment strategy is as seen in equation (6):

Model Prediction Matrix No model could achieve perfect predictions and wrong predictions are always in place. So prediction results could be classified into 4 types: real churned is predicted churned, real churned is predicted regular, regular is predicted regular, regular is predicted churned. The numbers of each type are N11, N10, N01 and N00, as illustrated in Table 1. Notes: p0 is the threshold value which is used to judge churned or not. If churn probability is bigger than p0, this customer could be identified as potentially churned. Accordingly, for different p values, N11, N10, N01 and N00 should have different value.

Cost/Profit Matrix When conducting churn prediction, simply higher prediction accuracy could not make sure the highest profit for the company. Because profits are different between predicting churn customer accurately and predicting regular customer accurately in customers churn prediction.

Table 2. Cost/Profit matrix real churned Cost Predicted churned

Cost Profit

Cost Predicted regular

388

regular

0 - Cost

- Profit

0

Total Pr ofit ( p 0 ) = (Pr ofit − Cost ) × N 11 ( p 0 ) + (0 − Cost ) × N 10 ( p 0 ) + (− Pr ofit + Cost ) × N 01 ( p 0 ) + (0 + Cost ) × N 00 ( P0 ) (6)

Therefore, for each threshold value p0, there is different total profit. When maximizing this equation, a threshold value p0 is obtained. Based on this p0, a churned customer group is identified for detainment strategies.

Detainment Response Hierarchy Analysis on Churned Customer The formulation of customer detainment strategy is largely based on detainment response hierarchy of churned customers. And this hierarchy is related to a variety of factors. Among these factors, customer churned tendency and customer detainment value play a major role. Customer churned tendency is measured by customer churned probability from the churn prediction model. A high churned probability indicates a high churned tendency. The major consideration of companies should be the combination of churned tendency and detainment value to achieve a best detainment result with the help of efficient usage of limited resources when designing detainment strategies.



Telecommunication Customer Detainment Management

Churned Customer Value Analysis This part will focus on churned customers value as customer churned tendency has been discussed before. Detainment value evaluation is based on the evaluation of a single customer’s consuming behavior. It is an indirect evaluation method without evaluating directly potential profit from the customer or evaluating directly the cost of detaining the customer. In this method, customer’s consuming behaviors before he churns have been reviewed comprehensively to evaluate this customer’s value. It is based this hypothesis: if a customer has a strong profitable and stable consuming behavior before he churns, this customer could be a high-quality customer and is worth to detain. Indicators that follow are used to analyze the customer detainment value: • Customer average telecommunication consumption amount • Customer telecommunication consuming stability Based on these two value indicators, customer detainment value could be evaluated comprehensively. Figure 5. Customer segments and customer detainment levels Emergency Level High

D

B

A

Medium

G

F

C

Low

I

H

E

Low

Medium

High

Detainment Response Hierarchy Analysis on Churned Customer Companies are restricted by cost as well as other factors when they try to detain customers. Normally, companies need to evaluate the detainment response level of customers to decide the priority of implementing customer detainment strategies. In this way, company could optimize the allocation of resources. In this research, the main thought is to consider both customer detainment value and customer churned tendency, which will provide foundation for designing customer detainment strategy. According to customer churn probability (emergency level) and customer detainment value (value level), we divide all potential churn customers into nine customer segments (named from A to I), showed as Figure 5. Furthermore, in order to determine the priority of each customer segment, three additional criterions are proposed, which are: Criterion 1: The higher the customer churn probability is, the higher the detainment priority is, on condition of the same customer detainment value; Criterion 2: The higher the customer detainment value is, the higher the detainment priority is, on condition of the same customer churn probability; Criterion 3: The priority of the customer churn probability is higher than customer detainment value. For example, the priority of D (high customer churn probability and low customer detainment value) is higher than E (high customer detainment value and low customer churn probability). Based on these criterions, priorities of nine customer segments detainment level can be determined at last, that is: A>B>C>D>E>F>G>H>I.

Value Level

389

Telecommunication Customer Detainment Management

Design Customer detainment Strategy Customer churn reason analysis is the first step for designing telecommunication customer detainment strategies. When the decline of customer relationship happens, the enterprise attributive analysis will be used to analyze the declining reason for designing customer detainment strategy.

Enterprise attributive analysis has these steps:

Step 1: To identify customer churn reason. Separately analyzes the declining reasons of customer relationship on different detain hierarchy. Step 2: To do enterprise attributive analysis. In an enterprise’s point of view, the controllability and the frequency of declining reason are bases for judging that whether the declining reason is necessary to improve, whether it can be improved, and how much it should be improved. The analysis processes are shown in Figure 6 and Figure 7.

Figure 6. Enterprise attributive analysis

Figure 7. The rules of determining controllability and frequency Controllable

Improving Degree

Controllability Analysis

Yes

High

High

Yes

Low

Low

No

Low

Usualness

390

Frequency

High

High

Medium

Medium

Low

Low

Telecommunication Customer Detainment Management

Figure 8. Classification matrix

Abandon strategy: choose a right time to terminate customer relationship, release the resource and try to provide a good impression for customers.

Y Fr equency

II Adequate Importance Area

IV Abandon Area

I High Importance Area

III Appropriate Importance Area

X C ont r ol l abi l i t y

Figure 9. Strategies in quadrants Y Fr equency

II Adequate I mportance Area Response Strategy

IV Abandon Area Abandon Strategy

I High Importance Area First-aid Strategy III Appropriate Importance Area Improve Strategy X C ontrolliablity

Step 3: Controllability and frequency analysis. Matrix of controllability and frequency is build to identify churn reasons. The value and position of churn reasons are analyzed quantitatively in this matrix. See Figure 8. Step 4: To formulate different detainment strategy on different churn customer segments. In this step, different strategies will be designed for 4 categories of customers that in the 4 quadrants separately. See Figure 9. First-aid strategy: intensify the controlling power, lower the frequency and recover customer relationship as soon as possible. Response strategy: try to transform low-controllable to high-controllable, regain customers and win the initiative in competition. Improve strategy: improve all related factors, lower the frequency to a low level, try to regain customers and make them useful for the development of companies.

Feasibility Analysis for Customer Detainment Strategy Questions about whether customer detainment strategy is feasible and whether detainment strategy will bring profit are answered by feasibility analysis. The long-term and short-term profit and cost are taken into comprehensive consideration. If the detainment strategy is feasible, the enterprise can implement this strategy; if not, this strategy should be improved or abandoned. On the side of profit, it firstly comes from the direct revenue after successful detainment. In other words, the income comes from those detained customers. The second source of revenue is the indirect revenue, including profit from new customers who are attracted in the detainment process, from avoiding the potential loss of churned customers, and from the invisible revenue from the implementation of strategies, e.g., invisible revenues from better enterprise image and better brand influence. Detainment cost includes not only the cost of implementing detainment strategy, but also the maintenance cost after successful detainment, such as network occupancy cost and related system building cost. In addition, the analysis includes some invisible revenue which could not be quantified. When comparing the profit with the cost of the detainment strategies, the setting that enterprise faces should be fully considered. For a developing telecom operator, direct revenue is focused and indirect revenue accounts for a low percentage when implementing detainment strategies. For an operator which just experienced bad social

391

Telecommunication Customer Detainment Management

Chart 1. 

N i is the number of customer who belong to type i



Pi (Retrieve) is retrieve rate which indicates the ratio of the successful detained customers number to type i customers number after company has implemented detainment strategy on type i customers.



ARPU i i s the expected ARPU ( Average Revenue Per User)value after the type i customer’s winning back.



Ti i s the period t hat company could get revenue from t he c ustomer after he/she has been successfully detained. Its unit is month.

IR(Indirect Revenue)

image matters, it may expect a significant amount of indirect revenue by implementing detainment strategy.

(1) Calculation for Direct Revenue Direct Revenue Direct revenue is an income that one type of customers (e.g. Type i customer) brings to the company after they has been successfully detained. DRi(Customer) = Pi(Retrieve) × Ni × ARPUi × Ti [see Chart 1.] (7)

Customer detainment strategies will not only bring profits to operators by improving satisfaction level of churn customers and attracting people surrounding these customers as new customers, but also reduce negative information broadcasted to the public from churned customers, and then reduce the customer churn rate and also the potential loss. In addition, indirect revenue also includes the invisible revenue from the improved brand and the corporate image. Analysis will be conducted in 3 aspects:

① IRi(Attractive) refers to the revenue from the

R(Indirect Revenue) is an income that detainment strategies bring to the company indirectly.

new customers who are attracted by the successful detainment strategy implementation.

Chart 1. ᧤1᧥ Pi ( Attractive) is the ratio of new customers who are attracted by successful retention strategy implementation to all new customers. Its value is between 0 and 1. ᧤2᧥ M (Attractive) is the average number of new customers per month after implementation of retention strategy. ᧤3᧥ ARPU A refers to the ARPU value of new customer. ᧤4᧥ Ti is the predicted retention period. Its unit is month.

ཱ IRi (Decrease) is the revenue from the reduced number of churned customers

who are detained by detainment strategy.

392

IRi ( Decrease)

Pi ( Decrease) u M ( Decrease) u ARPU B u Ti

(9)

᧤3᧥ ARPU A refers to the ARPU value of new customer. ᧤4᧥ Ti is the predicted retention period. Its unit is month.

Telecommunication Customer Detainment Management ཱ IRi (Decrease) is the revenue from the reduced number of churned customers

who are detained by detainment strategy.

Chart 3.

IRi ( Decrease)

z

Pi ( Decrease) u M ( Decrease) u ARPU B u Ti

(9)

Pi ( Decrease) is the ratio of reduced number of churned customer due to retention strategy to the all reduced number of all churned customers. Its value is between 0 and 1.

z

M (Decrease) is the average reduced number of churned customers after retention strategy compared to number of churned customers before retention strategy.

z

ARPU B is the ARPU value of reduced churned customers.

Explanation:

M (Decrease) in equation (9) indicates the monthly average reduced number of

emergencies, M(Decrease) will be negative and IRi(Attractive) = Pi(Attractive) × M(Increase) × churned customers after detainment strategy. However, if the monthly average aforementioned will not work. (8) of thethe ARPUA × Ti reduced number actually grows because marketing efforts by competingequations rivals While, in such a case, the implemented customer [see Chart 2.] detainment strategy still has a positive effect because there will be more churned customers ② IRi(Decrease) is the revenue from the reduced without detainment strategy. So, if it happens, the number of churned customers who are dereduced number of churned customers is required tained by detainment strategy. to be confirmed by market research. The revenue from these customers is equal to M(Decrease) IRi(Decrease) = Pi(Decrease) × M(Decrease) × multiplied by ARPUB and Ti. (9) ARPUB × Ti



[see Chart 3.]

Explanation: M(Decrease) in equation (9) indicates the monthly average reduced number of churned customers after detainment strategy. However, if the monthly average reduced number actually grows because of the marketing efforts by competing rivals or

③ Invisible Revenue (IR) is the revenue from detainment strategy which is hard to quantify. This revenue will facilitate company’s development in long term. It could be divided into several parts as follows: IRi(C) = Ri(Brand) + IRi(Company) [see Chart 4.]

(10)

The Chart should be positioned below Equation (12) p.392

Chart 4. ¾

C u means the monthly cost on each customer which is used to maintain the customer relationship, e.g. customer service cost

¾

N i indicates the number of churned customers in type i

¾

P᧤ i Retrieve) is the retrieve ratio of the number of detained

¾

customers in type i to the total customer number of type i after implementing retention strategy on type i customers. Ti is the predicted retention period. Its unit is month.

Signature____________________

Date________________________

393

Telecommunication Customer Detainment Management

Chart 5. z

Ci (Strategy ) is the strategy cost which is mainly from strategy itself, e.g. cost of mobile phone when mobile phone is free by promotion strategy or discounted cost in discounted strategy

z

C i ( Advertisement ) is the advertisement cost which is used to combine with retention strategy to improve the advertising effects

z

Ci (Human) is the human resource cost which is used to pay for the extra cost to recruit staff to do market investigation, analysis, advertising and communication with customer

z

Ci ( Agency) is the agency cost which is used to pay for the commission for agencies. These agencies are hired to deal with certain part of retention strategy.

z

Ci (Channel ) is channel cost which is used to manage the distribution channel of retention strategy.

ཱ Customer maintaining cost

Once a customer churned, company should C (Maintain) = Ni × Pi (Retrieve) × Cu × Ti (12) Customer maintaining cost is used to maintain ithe customer relationship with actively take some strategies to win him/her back, [see Chart 5.] successful detained customer and enterprise withinི predicted retention period after the Network Resource ི Network Resource CostCost customer has been regained by enterprise. e.g. more services and preferential treatment. (12) (Maintain) N uwill P (Retrieve ) u C uT Through communications,Ccustomers know Cost ③ Network Resource more about the brand and get rid of previous misresource cost which Cii(Network ) )is aisnetwork a network resource costequals whichthee C (Network ¾ C is the monthly costtheir on each customer is used to maintain understanding. When these customers spread Cwhich (Network) is athenetwork resource cost which i customer relationship, e.g. customer cost new understandings of brand and good image to serviceequals thewhole averagemobile cost pernetwork for the for the multiplied by the numb for the whole mobilecustomer network multiplied by t ¾ Ni is the number of type i churned customers public, recognition of the brand and good image whole mobile network multiplied by the number type i detained customers ¾ Pi (Re trieve) is Retrieve Ratio of predicted customers. customers. will come, and it will finally help popularize the of successful detained customers. number to all type i customers after implementing retention strategy on brand and attract new customers. type i customers. i

i

i

U

i

U

¾

① Implementation Cost Ci(Implement) refers to the implementation cost which is the major cost in implementation of detainment strategies. It will be discussed in several aspects as follows:

② Customer Maintaining Cost Customer maintaining cost is used to maintain the customer relationship with successful detained customer and enterprise within predicted retention period after the customer has been regained by enterprise.

394

ཱི Incline Cost Incline Cost ཱི Incline Cost

Ti is the predicted retention period. Its unit is month.

(2) Calculation of Detainment Cost

Ci(Incline) is in allusion to the customers who Ci (Incline ) is but in tend allusion to the customers who have not have not churned to churn because they C i (Incline) is in allusion to the customers who will get more profits through the enterprise’s because they will get more profits throughthrough the enterprise’s detainment strategies thanget maintain theprofits relationbecause they will more the en ship with the enterprise all the time. It will lead maintain the relationship with the enterprise all the tim maintain the relationship with the enterprise a to certain quantities of churned customers, and quantities ofof churned customers, and brings loss to en quantities and some brings some brings some loss tochurned enterprise.customers, This loss is called inclinecost. cost. discounted price and promotions. Incline incline e.g.e.g. discounted price and promotions. incline cost. e.g. discounted price and promotion Incline cost churned is the loss from these temporary temporary customers. temporary churned customers. churned customers.

ུ IT Cost ུ IT ITCost Cost

ITCost Costis is used to build IT system to maintain custome IT used to build the ITthe system to maintain IT Cost is used to build the IT system to maintain customer data and regain relationships of detainment relationships due to customer the implementation relationships due to the implementation of de C (IT ) . Cii (IT ) . In summary, the equation will be:

Telecommunication Customer Detainment Management

due to the implementation of detainment strategies. It is noted as Ci(IT). In summary, the equation will be: Customer Detainment Value = Detainment Revenue –Detainment Cost = Direct Revenue + Indirect Revenue – Implementation Cost – Customer maintaining cost – Network Resource Cost – Incline Cost – IT Cost = Direct Revenue + Revenue from the new customers + Revenue from the reduced number of churned customers + Invisible Revenue – Implementation Cost – Customer maintaining cost – Network Resource Cost – Incline Cost – IT Cost (13) Or: CustomerDetainingValue = DRi(Customer) + IRi(Attractive) + IRi(Decrease) + IRi(Brand) + IRi(Company) – Ci(Implement) – Ci(Maintain) (14) – Ci(Network) –Ci(Incline) – Ci(IT)

(1) Model-Based Feasibility Analysis for Customer Detainment Strategy Based on customer detainment value equation (14), customer detainment value can be calculated and used for reasonability and feasibility analysis.

Case 2: Direct Revenue < Detainment Cost, but Direct Revenue + Revenue from the new customers + Revenue from the reduced number of churned customers > Detainment Cost, which means IRi(Company) > Ci(Implement) + Ci (Network) + (16) Ci (Incline) + Ci(IT) But, DRi(Customer) + IRi(Attractive) + IRi(Decrease) > Ci(Implement) + Ci(Maintain) + Ci(Network + (17) Ci(Incline) – Ci(IT) In this case, direct revenue could not counteract all the detainment costs, but the revenue that direct revenue plus revenue from the new customers and revenue from the reduced number of churned customers are bigger than detainment cost. Regarding this result plus the invisible revenue, this strategy is still feasible. Case 3: Direct Revenue + Revenue from the new customers + Revenue from the reduced number of churned customers < Detainment Cost, but the result of Direct Revenue + Revenue from the new customers + Revenue from the reduced number of churned customers + Invisible Revenue - Detainment Cost is unknown, which means

Case 1: Direct Revenue > Detainment Cost IRi(Company) > Ci(Implement) + Ci(Maintain) + Ci(Network) + Ci(Incline) + Ci(IT) (15) In this case, detained customers will bring enough direct revenue to counteract all the detainment cost. Furthermore, there is some indirect revenue. So this strategy will of course make more benefit. It has been proved to be feasible.

DRi(Customer) + IRi(Attractive) + IRi(Decrease) < Ci(Implement) + Ci(Maintain) + Ci(Network) + (18) Ci(Incline) – Ci(IT) But DRi(Customer) + IRi(Attractive) + IRi(Decrease) + IRi(Decrease) + IRi(Brand) + IRi(Company) – Ci(Implement) – Ci(Maintain) + Ci(Network) (19) – Ci(Incline) – Ci(IT) is unknown. 395

Telecommunication Customer Detainment Management

In this case, the visible part in direct revenue and indirect revenue is lower than detainment cost while invisible cost has not been considered. It is required to analyze the feasibility regarding the practical situation. If there is a strong word of mouth effect, company will suffer a long-term loss from the difficulty in developing brand customers and building image without customer detainment strategies. But with strategy, word of mouth effect will facilitate the positive information communication, which helps popularize brand and company’s future development. In this case, even though company could not make direct visible revenue in short term, long-term revenue is very high and the strategy is feasible. Another case is that the word of mouth has a limited impact on people. Though the customer relationship is not recovered, negative information broadcast doesn’t have a strong effect. What’s more, even if it is recovered, it could not bring high invisible revenue for company. So the strategy is not feasible.

Case 4: Direct Revenue > Implementation Cost, but Direct Revenue + Revenue from the new customers + Revenue from the reduced number of churned customers < Detainment Cost, which means: DRi(Customer) > Ci(Implement) But DRi(Customer) + IRi(Attractive) + IRi(Decrease) < Ci(Implement) + Ci(Maintain) + Ci(Network) + (21) Ci(Incline) + Ci(IT) In this case, direct revenue seems to cover the implementation cost and even higher than the implementation cost. Many companies will judge the strategy is feasible. But in fact, these companies neglect the customer occupied network resource and in the long-term, customer maintaining cost and incline cost will grow higher and will make the combination of direct revenue and visible revenue in indirect revenue lower than detain-

Table 3. Strategy feasibility analysis based on customer detainment value Case 1

2

Customer Detainment Value

Feasibility Analysis

DR (Customer ) > C (Im plement ) + i i C ( Ma int ain ) + C ( Network ) + i i C ( Incline ) + C ( IT ) i i

Feasible

DRi (Customer ) < C i (Im plement ) +

Feasible

C i ( Ma int ain) + C i ( Network ) + C i ( Incline) But,

DRi (Customer ) + IRi ( Attractive) + IRi ( Decrease) > C i (Im plement ) + C i ( Ma int ain) + C i ( Network ) + C i ( Incline) + C i ( IT ) 3

DRi (Customer ) + IRi ( Attractive) + IRi ( Decrease) < C i (Im plement ) + C i ( Ma int ain)

Invisible revenue is r equired to consider.

+ C i ( Network ) + C i ( Incline) But,

DRi (Customer ) + IRi ( Attractive) + IRi ( Decrease) + IRi ( Brand ) + IRi (Company ) − C i (Im plement ) − C i ( Ma int ain) − C i ( Network ) − C i ( Incline) − C i ( IT ) 4

DRi (Customer ) > C i (Im plement ) But,

DRi (Customer ) + IRi ( Attractive) + IRi ( Decrease) < C i (Im plement ) + C i ( Ma int ain) + C i ( Network ) + C i ( Incline) + C i ( IT )

396

(20)

Invisible revenue, l ong-term and short-term r evenue a re required to consider.

Telecommunication Customer Detainment Management

ment cost. If invisible cost only accounts for a small percentage of all revenues, this strategy is not feasible practically. And as the time goes by, company will possibly suffer a higher loss. In this case, company should take practical situation, long term and short term revenue into consideration together to make a decision. In summary, aforementioned analysis is seen in Table 3.

Detainment Strategy Evaluation and Continuous Optimization Customer detainment value evaluation is the feedback phase after implementing customer detainment strategies. No matter how successful or not after implementation, company should compare, analyze and evaluate the implementation results with expected goal to find out the reasons for any possible deviation from expected goal and propose guidance and suggestions for detainment response and improvement of detainment strategies. The evaluation will make sure resources are used reasonably and higher economic revenue are gained than attracting new customers, which will together form the closed loop of customer detainment management. The evaluation of customer detainment strategies could be monitored by these 2 indicators: • Customer Churned Rate Customer Churned Rate is the ratio of the customers who transfer from one telecom operator to another or from one brand to another brand in the same telecom operator to all customers. If there is a huge decline after implementations without the affection from other sources, the strategy is proved to be effective. If customer churned rate is still high, the strategy is proved to have some problems and is required to improve. •

ARPU

Comparing the ARPU of certain groups of customers before and after the implementation of customer detain strategies will show whether the strategies enhance the customer value. If there is a significant rise of ARPU without any impacts from other sources, the strategy is proved to have a significant effect on maintaining customer relationships and to enhance customer value. If not, the strategy has the limited effect on company revenue and is required to improve. While evaluating the customer detainment strategy, some other indicators could be taken into account, e.g. ROI (Return of Investment). Customer churned rate and ARPU are the two simplest and most practical indicators among all indicators. On one hand, they tell whether strategy is effective on preventing customers from churning; on the other hand, they help judge whether strategy brings more revenue. Therefore, the effect of strategy can be evaluated quantitatively by these 2 indicators. However, customer churned rate are not in line with ARPU When customer churned rate reduces, ARPU may be lower because of some discount strategy. So company needs to evaluate them comprehensively to realize the strategy effect. What is obvious is that a company does not want to see the situation of rising customer churned rate and reduced ARPU happen simultaneously, which indicate the failure of the detainment strategies. On the other hand, the company would love the simultaneous reduced customer churned rate and rising ARPU, which indicate the success of the detainment strategies.

Future Trends Competition in the telecom industry will be fiercer because of the deregulation in the global telecom industry, more rapid development of new technologies and services, and convergence of the telecom network, computer network, and television network. Telecom operators’ customer management will inevitably transform from single-point static

397

Telecommunication Customer Detainment Management

customer management to life circle management. New customer development should focus on high value-added potential customers who are hard to churn. Old customer detainment should focus on high value and stable customers. Customer detainment management should focus on detaining high value and stable customers who suffer from the improper customer detainment activities. The churned characteristics which are gained from customer detainment management could be used in new customer development to avoid developing customers who are easy to churn. Telecom customer life circle management will be the most important part in telecom customer management in the future. The emphasis of telecom customer life circle management should be on the overall good performance in all phases of the customer life cycle not a perfect performance in only one phase. In the phase of customer detainment management, further research and practices are required. Current research and practice focus mainly on customer churn alarm, and there are only a few studies on customer detainment value evaluation. There are some practical experiences by companies, but research on how to formulate emergent detainment strategy and long-term detainment strategy is lacking. There is also a lack of in-depth research on evaluation methods and resource analysis for detainment strategy. These issues should be the focus of both research and practice in the future. Regarding our research methodology, aside from the quantitative analysis of customer churn alarm, the remaining parts of customer detainment management are mainly qualitative. How to apply quantitative analyses to telecom customer detainment management is worth studying. For the management practice, some excellent cases on customer detainment are worth sharing and collecting.

398

Conclusion A comprehensive methodology of customer detainment management is proposed in this chapter. This methodology was developed based on the author’s management consulting experience with several China telecom operators. Each phase in this methodology has been explained in detail, especially the discussion on the missing points in the current literature. A good management performance will be gained when this methodology is implemented prudently. Customer detainment management is not the ending phase of customer life cycle management. It should be distilled into the whole customer management processes including new customer development, customer value upgrading, and customer detainment.

Acknowledgment The research work in this chapter was supported by the National Natural Science Foundation of China (Project No.: 70701005), the Specialized Research Fund for the Doctoral Program of Higher Education of the People’s Republic of China (Project No.: 20070013014), and the Open Research Fund between Beijing University of Posts and Telecommunications and IBM.

References Au, W., Chan, C. C., & Yao, X. (2003). A novel evolutionary data mining algorithm with applications to churn prediction. IEEE Transactions on Evolutionary Computation, 7, 532–545. Bloemer, J., Brijis, T., & Vanhoof, K. (2002). Comparing complete and partial classification for identifying customers at risk. International Journal of Research in Marketing, 20, 117–131.

Telecommunication Customer Detainment Management

Datta, P., Masand, B., & Mani, D.R. (2001). Automated cellular modeling and prediction on a large scale, Issues on the Application of Data Mining, (pp. 485–502). Hadden, J., Tiwari, A., Roy, R., & Ruta, D. (2007). Computer assisted customer churn management: State-of-the-art and future trends. Computers & Operations Research, 34(10), 2902-2917.

mining approach. Expert System with Application, 23, 103-112. Yan, L., Dodier, R., & Mozer, M. (2003). Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic. In F. Tom & M. Nina (Eds.), Proceeding of the Twentieth international Conference on Machine Learning, (pp. 848-855). Washington: AAAI Press.

Kim, M., Park, M., & Jeong, D. (2004). The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunications services. Telecommunications Policy, 28, 145–159.

Yan, L., Wolniewicz, R., & Dodier, R. (2004). Predicting customer behaviour in telecommunications. IEEE Intelligent Systems, 19, 50–58.

Kristof, C., & Dirk, V. (2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques, Expert Systems with Applications, 34(1), 313-327.

Key Terms

Lian, Y., Richard, H. W., & Robert, D. (2004). Predicting Customer Behavior in Telecommunications, Intelligent Systems, 19(2), 50-58.

Customer Churn: Customer’s switching from this services or goods provider to another.

Meyer-Base, A., & Watzel, R. (1998). Transformation radial basis neural network for relevant feature selection, Pattern Recognition Letters, 19, 1301–1306. Mozer, M. C., Wolniewicz, R., & Grimes, D. B. (2000). Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry. IEEE Transactions on Neural Networks, 11(3), 690–696.

Churn Alarm Model: The mathematical model or data mining model for predicting customer churned tendency.

Customer Detainment Management: A management methodology containing customer management process, strategy and evaluation which company uses to prevent customer from churning. Customer Detainment Strategy: The management strategy which company uses to avoid customer from churning.

Ng, K., & Liu, H. (2001). Customer retention via data mining, Issues on the Application of Data Mining. Artificial Intelligence Review, 14(6), 569–590.

Customer Relationship Decline Phase: The last phase of customer relationship life circle management (Recognition Phase, Development Phase, Mature Phase and Decline Phase). When customer has the signs to churn, customer relationship enter Decline Phase.

Shu, H. Y., & Qi, J. Y. (2004). Telecommunication Customer Life Cycle Management. Beijing University of Posts and Telecommunications Press.

Detainment Response Hierarchy Analysis: To decide the detainment priority of churned customer in the view of company.

Wei, C. P., & Chiu, I. T. (2002). Turning telecommunication call detail to churn prediction: a data

Enterprise Attributive Analysis: It is the analyzing method focusing on customer churned reason in the view of company. 399

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Chapter XXV

How to Plan for an Upgrading Investment in a Data Network? Frédéric Morlot Orange Labs, France Salah Eddine Elayoubi Orange Labs, France

Abstract We illustrate how a mobile data network operator can plan an upgrading investment to anticipate explosions of the demand, taking into account the expected profit and the customer satisfaction. The former parameter grows with the demand, whereas the latter sinks if the demand is too high, as throughput may collapse. As the equipment price decreases with time, it may be interesting to wait rather than to invest immediately. We then propose and discuss two methods that help in making the decision. The first one is an actualization algorithm, where the upgrade should be performed when the loss of profit, derived analytically, exceeds the expected discount. The second is a real option-like strategy to hedge against the risk that the investment has to be anticipated. The evaluation of the investment date is then performed, in the latter, by a backward dynamic programming approach, using recent improvements based on least-squares estimations, whereas, in the former, a forward actualizing algorithm is investigated through simulations.

INTRODUCTION As new multimedia applications are introduced in the market, the traffic is significantly growing in mobile networks. In particular, data flows are growing exponentially, as they have been doing since the middle 90s in the Internet. To face these soaring volumes of data to be transferred,

mobile operators must periodically upgrade their equipments to offer higher throughputs and avoid blocking problems. However as the demand does not increase steadily and must be considered as partly random, the upgrade dates are difficult to be forecast (Morlot, et al., 2007). In this chapter, we consider upgrade investments in a HSDPA (High Speed Downlink Packet

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How to Plan for an Upgrading Investment in a Data Network?

Access) cellular network. Note that, when demand increases, the data communication duration becomes longer and longer for each user until the network is saturated. The individual throughput experienced in the network may become very small. On the other hand, as the demand rises, the operator increases its profit. When the network starts experiencing saturation problems, throughput and profit may fall. The operator must then upgrade its network by adding new frequency carriers, facing the following trade-off: •

•

The later the investment, the lower individual throughputs and customer satisfaction. Permanent non-satisfaction will result into churn and additional loss of profit. The sooner the investment, the more expensive the costs of upgrade elements.

This chapter aims at modeling analytically the trade-off. We first derive analytical values for capacity, individual throughput and satisfaction as a function of the demand, and use them to calculate operator's profit, taking into account randomness of the rising demand, and decrease of network element costs according to time. We then propose two decision-making methods. In the first method, we develop an actualization algorithm that calculates the optimal investment time using the above described analytical modeling, as in our previous work (Morlot et al. (2007)). We base our method on the idea that the upgrade should be performed when the loss of profit, derived using analytical capacity expressions, exceeds the expected discount. As time goes by, we have realizations of the daily demand. These values can thus be used to derive a more precise optimal date than the one we found at time t = 0 assuming demand randomness. Instead of calculating expectations, we can now take in account what really happens during the period. This is the idea of the actualization algorithm, where the expected investment time is calculated using simulations.

We then introduce a second, more analytical method, based on real options to hedge against the risk that demand evolves in an unexpected way, leading to a premature investment decision or a too late one. To perform that, we model the investment as a virtual American call that gives its owner (the mobile operator) the right, but not the obligation, to buy an equipment, until a maturity date. Given the profit analytical model and the option’s parameters, we propose a backward dynamic programming method to obtain the expected best investment date.

BACKGROUND The problem of investment under uncertainty has been investigated in several domains. Longstaff & Schwartz (2001) introduced a pricing method for american options in general (this method has been approved in Protter, Clément & Lamberton (2002)). In Laughton (1991), the authors introduced a real options method to evaluate investments in oil fields. A real options framework was also proposed for evaluating investments in sustainable development projects (see Salahaldin & Granger (2005) and Salahaldin (2007)). For a detailing of real option types and correlated bibliography, see Trigeorgis (1993), and for a general economic introduction, see Dixit & Pindyck (1994). In the telecommunications field, the applications were scarce, although real options are relevant to telecommunications in several areas: strategic evaluation, estimation and cost modelling, as indicated in Alleman (2002). D’Halluin, Forsyth & Vetzal (2007) presented a work on a method to determine the best investment date in a wireless network. His approach was based on dynamic programming, but he didn’t introduce any risk hedging method nor an option pricing. This chapter aims at showing, using the example of an HSDPA data network, how the investment decision can be evaluated based on a calculation of the expected profit.

401

How to Plan for an Upgrading Investment in a Data Network?

( X (t , Wt ) = x0 e

THE BASIC MODEL: OPERATOR’S PROFIT AND INVESTMENT COST The operator profit depends on the amount of data flowed by the network. However throughputs depend on a large number of parameters and are difficult to calculate. The profit thus depends on the following parameters: •

•

The mean traffic demand per cell (in Mbits/ sec/cell). We denote it by Xt , where the time t = 0,1 ... T varies discretely, for example day by day. [0, T] stands for the considered time period. After T, one considers that our network is becoming obsolete. The customer satisfaction before and after the upgrading (St1 and St2)

2 α −σ

2

)t +σ W , t

t ∈ R+

where Wt is a standard brownian motion, α is the trend of the demand and σ is its volatility.

Customer Satisfaction To evaluate the customer satisfaction, let us first compute the flow throughput gt(r) a user can expect at distance r from the center of the cell, as carried out in Bonald & Proutière (2003). The resource of a single downlink data channel is time-shared between active users. Denote by Φu the fraction of time the BS transmits to user u, with ∑ Φ u = 1. The data rate of user u is then u

Traffic Demand

Cu(r) =C(r)Φu, where C(r) is the peak data rate, obtained in the absence of any other user in the cell, i.e., for Φu = 1. When there are x users, the

We assume that the network is formed by circular cells of radius R, with a uniformly distributed demand. We have:

“fair power” sharing is defined by Φ u = 1 . We x have:

Xt = lt × E[x],

 Z Γ(r )  C (r ) = min  C0 , ⋅ , b η + I (r )  

where lt is the arrival rate per cell at the date t and E[x] is the mean size of a typical data flow. In the following we assume that E[x] remains stable during [0, T], so that Xt is proportional to lt. This model is strictly equivalent to the case where the number of active users is constant, but they initiate connections more often. To model the evolution of Xt, let us consider it as the daily sampling of a continuous stochastic process X (t , Wt )t∈R+. Usually, one monitors the 24 demands over one hour each, keeps the second or third highest, and multiply it by a given factor. As many random phenomena related to a social behavior (e.g. Salahaldin & Granger (2005), Salahaldin (2007)), we assume that X (t ,Wt ) is a geometric brownian motion (see El Karoui & Gobet (2003) page 88):

402

where: •

• • • • •

C0 is the maximum peak rate (which depends on channel bandwidth and coding efficiency) Z is the cell chip rate b is a lower bound for energy-per-bit to noise density ratio (Eb/N0) Γ(r ) is the path loss between the BS and user u h is the thermal noise to received power ratio I(r) is the interference to received power ratio.

How to Plan for an Upgrading Investment in a Data Network?

We define the cell load as (see Bonald & Proutière (2003)):

For example, b can be chosen as: b = log(2) • g1/2

R

ρt =

X t 2πrdr . πR 2 ∫0 C (r )

•

•

If rt > 1, the cell is overloaded and one can show (Bonald & Proutière (2003)) that the number of active users grows indefinitely; any individual data rate tends to zero, and the cell is saturated If rt < 1, the cell is underloaded and the number of active users tends to a finite stationary regime.

We are naturally led to introduce: −1

X max

 R 2πrdr   , = πR  ∫   0 C (r )  2

such that rt = Xt / Xmax. Hence ρt < 1 ⇔ X t < X max. It is easy to show that the average throughput of the cell is given by (Bonald & Proutière (2003)): γ t = (X max − X t ) , +

(2)

where x+ = max(x, 0). Note that γ t = 0 if and only if the cell is saturated. Now we can compute the customer satisfaction, which can reasonably be supposed to depend on γ t . Since subjective satisfactions have been shown to be more sensitive to small variations at low throughputs than at high throughputs, Enderlé and Lagrange propose in Enderlé & Lagrange (2003) to model the customer satisfaction as a negative exponential function of the throughput: St = e

+

− β ( X max − X t )

.

where g1/2 is the throughput value ensuring a satisfaction of 50%. Once again, note that St = 0 if and only if Xt ≥ Xmax i.e., if and only if the cell is saturated.

Daily Profit Let us recall that Xt is sampled day by day, for example during the second or the third highest peak hour. Within 24 hours, the operator transmits m min(Xt, Xmax) to active users, where m is a multiplicative factor between the peak hour and the whole day. Typically, we can consider that the peak hour represents 25 % of the total daily transfer. This leads to µ ≈ 4.3600 = 14000 sec. Since taxation is applied to the volume of transfers and not to the duration, the gross daily profit per cell is given by: pgross = δm min(Xt, Xmax), where δ is the transfer price (say in $/Mbit). However the gross profit should be weighed by the customer satisfaction to account for the quality of the communications. The net profit is thus calculated as the product of pgross by St: +

π net = δµ min( X t , X max )e − β /( X max − X t ) .

If St = 0, i.e. if the cell is saturated, the net profit is null. If the satisfaction is maximal, i.e., St = 1, the net profit is equal to the gross profit. To sum up we have: δµ min( X t , X max )e − β /( X max − X t ) πt =   0

+

if X t < X max otherwise

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How to Plan for an Upgrading Investment in a Data Network?

Figure 1. Daily Profit generated by demand. The solid line represents gross profit and the dotted line represents net profit. Xmax = 3 Mbits/sec/cell, δ = 0.1 $/Mbit, m = 14000 sec, b = 0.7 Mbit/sec (which corresponds to γ1/2 ≈ 1 Mbit/sec)

Intuitively, as the demand rises, Xt will increase as will the profit (Figure 1). Then, the profit will decrease because the unsatisfaction effect becomes dominant. If no upgrading action is taken, the profit will progressively tend to zero. Once the operator decides to upgrade, he can install additional transmitters operating on different frequency bands. In such a case we obtain a higher value of Xmax, so that: +

Upgrading Investment The upgrading cost is a decreasing function of time. The decrease of the cost is due to many factors, for example the R&D progress, and also the serialization in the manufacturing chain. Moore’s law states that electronic devices’ capacity doubles every 18 months. So in this paper we assume it decreases exponentially:

π ' t = δµ min( X t , X ' max )e − β /( X max − X t ) .

K(t) = K0 e–εt

Total Profit

where ε is the depreciation rate.

'

If we denote the investment date by t0 the total profit PT (t0) actualized at the date t=T is: t0 −1

T

t =0

t =t 0

EVALUATING THE INVESTMENT BY AN ACTUALIZATION ALGORITHM

P T (t 0 ) = ∑ eζ (T −t )π t + ∑ eζ (T −t )π ' t ,

Total Profit

where z is the actualization rate. For simplicity, we assume that z is constant during the period [0, T].

As we have now derived pt analytically, we can compute numerically the expectation of PT (t0) given t0 using the Monte Carlo method. Results for the calculation of the daily profit calculated using Scilab are shown in Figure 2.

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How to Plan for an Upgrading Investment in a Data Network?

We observe that the higher s is , the more important the risk is and the sooner the maximal value of the expected profit is reached. Additionally, the higher s is, the slower the curve tends to zero. When s becomes paramount, the curve flattens out. From the previous simulation, we can deduce the total profit shown in Figure 3. We observe that the expected profit diminishes as the volatility increases, because of the risk. To summarize the results:

•

•

For a given value of s, the earlier the investment, the happier the consumers, and the higher the profit; At a given date, the higher s, the lower the profit, since the system can be saturated earlier.

However, when we take the investment cost into account, the number to maximize is what we call the total Profit-minus-Cost (PMC), actualized at date T:

Figure 2. Expected Daily Profit during the period. Parameters are identical to those used in former figures

Figure 3. Total Expected Profit. Xmax = 8 Mbits/sec/cell after the upgrade. z = - log(0.95)/365 day-1, which corresponds to a 5% / year actualization

405

How to Plan for an Upgrading Investment in a Data Network?

Figure 4. Expected PMC during the period. K0 = 300 k$ and ε = -log(0.5)/365, which corresponds to a 50% / year cost decrease

PMC (t 0 ) = P T (t 0 ) − K 0 e (ζ T −(ε +ζ )t0 .

Note that generally ε > z, so that ε + ζ ≈ ε. Results when taking the K(t) component in our simulations and results are shown in Figure 4. Again we show that the higher the volatility is, the lower the expected profit is. This result was expectable because of the increased risk. Furthermore, we see that the optimal investment date decreases according to the volatility, as shown in Figure 4. However, works on investment under uncertainty obtain the opposite result Salahaldin & Granger (2005). In fact, as will be shown in next section, the significant value to observe is

the optimal actualized investment date, and we will observe the opposite trend.

Strategy As time goes by, we have realizations of the daily demand. These values can thus be used to derive a more precise optimal date than the one we found at t = 0 assuming demand randomness. Instead of calculating expectations, we can now take in account what really happens during the period. We can implement the following algorithm: each day t ∈ [0, T], we perform deterministic calculations over [0, t] and expectations over [t, T], with an initial value xt of traffic demand which is

Figure 5. An example of the traffic demand evolution Xt

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How to Plan for an Upgrading Investment in a Data Network?

Figure 6. Best investment date during actualization algorithm in the random case (s = 0.05 day-1/2), for the trajectory in Fig. 5. Here, investment will take place at around t = 60 days. When Xt does not grow as fast as expected, the actualized investment date is postponed. But as soon as Xt has sufficiently grown, the actualized date is stabilized

now a deterministic parameter. Each computation thus provides us with a new investment date t0 ∈ [0, T]. In other words, t0 is daily actualized. When t0 becomes close to t, it is time to invest. Note that such a situation t0 → t will inevitably happen by continuity, since at the end of the process we have t=t0=T. Interestingly we can take the upgrading delay into account : if for example we need 1 month of delay for the deployment, we will plan it as soon as t0 – t ≤ 30 days.

Because of the randomnes, we can observe some fluctuations before t0 becomes stuck to t (see Figure 6). To examine the impact of randomness on the investment date, we simulate several possible scenarios, in other words, several possible trajectories of the brownian demand. For each trajectory, we apply the actualization algorithm and we compute a final result, averaged over all the simulations (see Figure 7): now, we are in accordance with classic investment studies.

Figure 7. Mean final date returned by actualization algorithm regarding volatility. As expected, this date becomes later while volatility is growing

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How to Plan for an Upgrading Investment in a Data Network?

cally. We then use Monte-Carlo simulations as follows:

EVALUATING THE INVESTMENT BY A REAL OPTIONS METHOD

•

In this section, we present an alternative way to compute the optimal investment date. As shown above, there is a tradeoff between the growth of the demand (encouraging to invest) and the depreciation of the equipment cost (encouraging to wait). Then the risk is to be led to invest while the equipment is still expensive. When is the investment going to be exercised ? It depends on the additional profit expected from investing to upgrade the network: at least, this additional profit has to be greater than K(t). At date t, it can be expressed as follows:



• T  S t = E  ∫ e −ζ ( s −t ) (π ' ( s,Ws ) − π ( s,Ws ))ds Ft , t 

(3)

which we can rewrite as St = v(t,Wt ), with: T

[

]

v(t , x) = ∫ E e −ζ ( s −t ) (π ' ( s,Ws ) − π ( s,Ws )) Wt = x ds. t



(4)

Facing the decision to invest or not, the operator’s strategy is to compare the profit realized if investing with the value of waiting, typically to check that the traffic is not going to decrease unexpectedly which would make the upgrading expenditure a sunk cost. This appears to be the classical problem of finding the exercise strategy for an American option, with (St – K(t))+ as the option’s payoff, denoted by Z(t): Z(t) = max(St – K(t), 0)



(5)

Monte-Carlo Simulations to Generate the Underlying Asset Calculating St involves a complex integration (equation (3)) that cannot be performed analyti-

408

First we compute v(t,x) with equation (4) for t ∈ [0, T] and x ∈ [wmin, wmax]. To bind efficiently the brownian motion, we use a result of El Karoui and Gobet (see El Karoui & Gobet (2003), Proposition 1.3.8.): P(supt ≤ T|Wt| ≥ c) ≤ 2P(|Wt| ≥ c), which tends to 0 extremely rapidly when c → ∞. Hence, if we choose correctly our parameters so that the critic lines Wt = wmax and Wt = wmin lie far enough from the line w = 0, the probability to reach them during the experiment will be extremely low. Then, in practice, we will consider that (Wt) remains almost surely bounded. Then we discretize time: t = t0 ...tN with t0 = 0 and tN = T = Nδt. After that we simulate J trajectories of St: the j-th trajectory is denoted by S jand has the value Snj at time tn = nδt. More precisely, we simulate J trajectories of the brownian (W j), and then we compute Snj = v(tn, Wnj by interpolating v(t,x). This is far more efficient than computing directly the integral, especially if we want to simulate a large number of trajectories, since we do not have to compute v each time again.

Continuation Value and Decision Tree Algorithm At time T, the operator invests if ZN>0. More generally, at a time tn < T, the operator has two alternative choices: either invest now and get Zn, or wait and get the expected continuation value, denoted by Cn. The generated cash-flow is then given by: Fn = max(Zn, Cn). We already know Zn by (4). As for Cn, we use the Least Squares Monte-Carlo (LSM) approach defined by Longstaff & Schwartz (2001).

How to Plan for an Upgrading Investment in a Data Network?

This approach consists in writing the expected continuation value Cn as a general function of Sn (in our case we took a 2-degree polynom), taking information from the J cash-flows at tn + 1 and using the fact that: Cn ( S ) = e −ζ δ t E[ Fn +1 S n = S ],

where Fn + 1 is the (random) cash-flow of the option at tn + 1. To obtain recursively Cn, we can write the following algorithm: • •

At tN, for each trajectory j = 1…J, calculate the cash-flow FNj = ZNj. Move one period back to tN – 1. For each S j , check if the option is “in the money”, i.e. if ZjN – 1 > 0. If it is the case, calculate the continuation value C jN – 1 using the cash-flow if investment is delayed: C Nj −1 = e −ζδt FNj. Estimate then the general expression of C N – 1(S) by the LSM algorithm. This consists in regressing the found values C jN – 1 on a constant, S and S2, as in Longstaff & Schwartz (2001).

Let us denote the estimated expression by Cˆ N −1 ( S ). The estimated cash-flow at N-1 is then given by:

(

)

FNj−1 = max Z Nj −1 , Cˆ N −1 (S Nj −1 ) .

If it is optimal to exerce at tN – 1, then by convention FNj becomes 0 (because the option can only be exercised once). •

For each time tn, repeat the same process until n = 0.

Let us denote by ON the set of the j such that ZNj = 0, and by IN the set of the j such that ZNj > 0. Here is a summary of the whole algorithm:

Expected Investing Time Finally, we obtain for each of the J trajectories a best investment date Tinvj . Averaging the Tinvj s, we obtain the expected investing time:

Table 1. 1. simulate J trajectories (S j) 2. for j = 1…J, put FNj = Z Nj 3. for n = N-1…1, 0 : for j = 1…J, calculate Z nj : -

if Z nj = 0 , j ∈ On

if Z nj > 0 , j ∈ I n process On and I n separately: -

∀j ∈ On : put Fnj = e −ζ δ t Fnj+1

∀j ∈ I n : -

-

regress Cnj = e −ζ δ t Fnj+1 on 1, S and S2 t o obtain a 2 -degree polynom Cˆ n ( S ) put F j = max Z j , Cˆ ( S ) n

(

n

n

)

if Z > Cˆ n ( S ) , then n i s the new investment d ate, s o put Fmj = 0 ∀m > n j n

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How to Plan for an Upgrading Investment in a Data Network?

E[Tinv ] ≈

1 N

J

∑T j =1

j inv

.

(6)

Numerical Results In order to illustrate our algorithm, we applied it using the free simulator Scilab (see Gomez (1999)). We considered a HSDPA pure data network with a random growing demand, as described in section Traffic Demand. We used the following parameters for our computation: • • • •

• •

The investment can take place until T = 150 days. The equipment's price decreases with a rate ε of 50% per year. The actualization rate z is fixed to 5% per year. The traffic demand starts at x0 = 1.2 Mbit / sec / cell, and increases with a drift fixed to a = 0.54% per day. Its volatility varies between 0.005 and 0.02 day–1/2. Its maximal value is fixed to Xmax =3 Mbit/sec/cell before the investment, and to X 'max =8 Mbit/sec/cell after the investment. The data transfer price is fixed to δ = 0.1 $/Mbit. We take a satisfaction parameter of b = 0.7 Mbit/sec/cell.

Figure 8. Investment date

410

•

We simulate 5000 different trajectories of the asset.

On Figure 8, we represent the investment date versus K0. Recall that the date is obtained with equation (6), where K0 implicitely appears in generalized function Z (see equation (5)). It appears that the investment date is very low for lower values of K0. This happens because the equipment is already quite cheap at the beginning, thus it is all the more interesting to invest early. Of course, the higher K0 is, the later the investment takes place, since one has to wait longer until the equipment becomes affordable.

Comparison of both methods In this section we compare results obtained with the actualization algorithm on the one hand, and the backward programming method on the other hand, with K0 = 300 k$ and s = 0.01 day–1/2. •

•

With the former method, we find an expected investment date of 42.04 days with a standard deviation of about 0.1 day. With the latter, we find an expected investment date of 39 days with a standard deviation of about 1.15 day.

How to Plan for an Upgrading Investment in a Data Network?

The results are very close, and thus, both methods can be used for estimating the investment date. However, the real option method has the advantage of being quicker in terms of computation duration.

ο

Future trends • The above analysis shows that uncertainty is an important issue while dealing with infrastructure investment in telecommunication networks. In fact, it has been shown that waiting is the optimal choice in several cases. The methods presented herein should be of interest for operators, allowing them to make optimal decisions as to when upgrade their radio networks. So far, the decision methods have been illustrated in a particular situation. However it could be applied to a wide range of different situations. •

First of all, we could generalize the analytical model proposed in section "Basic Model". For example, we could introduce: ο Admission control: if the network guarantees to each user a minimal data throughput, some users may be blocked. In that case, the satisfaction St depends on the blocking rate instead of the throughput. Bonald & Proutière (2003) gives the blocking rate by:

B=



ο

ρtm , 1 + ρt +  + ρtm

where rt is the cell load and m is the maximum allowed number of users in one cell. Then we would assume that the customer satisfaction decreases exponentially according to blocking rate. Different power allocations. Then we would have to balance satisfaction over the cell by the probability density function of the user position.

•

Discontinuities and randomness in the investment cost curve. So far, we have supposed this latter curve being continuous and deterministic, but due to R&D’s breakthroughs, it may not be the case. Of course, we would have to adapt the PMC’s computation. Furthermore, we could imagine the operator planning more than one investment (e.g. adding WiFi hotspots): a multi-investments model would have to be deployed. Basically, this could consist in introducing two investment dates t1 and t2, corresponding to two technologies characterized by X 'max and X ''max, with Xmax < X 'max < X ''max . Both methods may then be turned into 2-dimensional versions. A last generalization consists in effectively buying an option from a financial institution, that gives us the right to buy the equipment at a fixed price, possibly lower than the real market price. The backward analysis can be extended to price this option, for example with a risk-neutral approach.

Conclusion In this chapter, we developed two methods to evaluate upgrading investment date in a data network. In the first method, we considered that this date is the result of a compromise between the decrease of upgrade investment cost with time and the loss of profit generated by insufficient capacity. The upgrade should hence be performed when the loss of profit, derived using analytical capacity ex- pressions, exceeds the expected discount. We then developed an actualization algorithm that calculates the optimal investment time using the above described analytical modeling. The second method is based on a real options approach as the operator has the right, but not the obligation, to perform the upgrading investment, under the demand (traffic) uncertainty. We

411

How to Plan for an Upgrading Investment in a Data Network?

showed how the problem can be formulated as a real options problem. In fact, facing the decision to invest or not, the operators strategy is to compare the profit realized if investing with the value of waiting, typically to check that the traffic is not going to decrease unexpectedly which would make the upgrading expenditure a sunk cost. This appears to be the classical problem of finding the exercise strategy for an American option. We thus developed a dynamic programming algorithms that calculates the optimal investment date and the expected operator’s profit. We finally compare the results obtained from both methods and show the advantages and drawbacks of each of them.

Acknowledgment The work was supported by ANR project Winem.

REFERENCES Alleman, J. (2002). A New View of Telecommunications Economics. Telecommunications Policy. Bonald, T., & Proutière, A. (2003). Wireless Downlink Data Channels: User Performance and Cell Dimensioning. Proceedings of ACM MobiCom’03, September 14–19, 2003, San Diego, California, USA. D’Halluin, Y., Forsyth, P. A., & Vetzal, K. R. (2007). Wireless Network Capacity Investment. European Journal on Operational Research, 176(2007), 584-609. Dixit, A. K., & Pindyck, R. S. (1994). Investment under Uncertainty. Princeton, NJ: Princeton University Press.

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El Karoui, N., & Gobet, E. (2003). Introduction au Calcul stochastique, première partie, Imprimerie de l’Ecole Polytechnique. Enderlé, N., & Lagrange, X. (2003). User Satisfaction Models and Scheduling Algorithms for Packet-Switched Services in UMTS. Proceedings of IEEE VTC spring, April 2003. Gomez, C. (1999). Engineering and Scientific Computing with Scilab. ISBN: 978-0-8176-40095, 1999. Laughton, D. (1991). The Valuation of Offshore Oilfield Development In Leases. Advances In M. Breton &G. Zaccour (Eds.),Operations Research in the Oil and Gas Industry and Editions Technip (pp.63-82), Paris 1991. Longstaff, F. A., & Schwartz, E. S. (2001). Valuing American Options by Simulation: A Simple Least-Squares Approach. The Review of Financial Studies, 14(1), Spring. Morlot, F., Fourestié B., & Elayoubi, S. E. (2007). Optimizing the date of an upgrading investment in a data network. Proceedings of the IEEE Vehicular Technology Conference IEEE VTC-fall 2007, Baltimore, October 2007. Protter, P., Clément, E., & Lamberton, D. (2002). An analysis of a least squares regression method for American option pricing. Finance and Stochastics, Springer, 6(4), 449-471. Salahaldin, L. (2007). A Numerical Algorithm for Decision-making in Sustainable Transport Projects Investment. Proceedings of the 11th Annual International Conference on Real options, Berkeley, CA, June 2007. Salahaldin, L., & Granger, T. (2005). Investing in Sustainable Transport to Relieve Air Pollution under Population-Growth Uncertainty. Proceedings of the 9th Annual International Conference on Real options, Paris, June 2005.

How to Plan for an Upgrading Investment in a Data Network?

Trigeorgis, L. (1993). The Nature of Options Interactions and the Valuation of Investments with Multiple Real Options. Journal of Financial and Quantitative Analysis, 28(1), 1-20.

Key Terms Actualization Algorithm: This is the first method presented above. If an optimal investment date is found at a given time, then it is wise to actualize it regularly in the future, taking into account new information about traffic evolution. Dynamic Programming: After simulating several trajectories of the traffic demand, dynamic programming consists in building a decision tree in a time-backward manner. Operator Gross Profit: This is the cash the operator can expect to charge his users for downloading a given amount a data.

Operator Net Profit: This is equal to gross profit ponderated by user satisfaction. PMC: This means ”Profit minus Cost”. When the operator considers his total profit over a given period, taking into account a necessary investment, he has to deduce the equipment cost. Real Option: It gives the operator the choice between investing at once, or waiting for hopefully better conditions. Upgrade Investment: If the user satisfaction becomes low, the operator net profit decreases, and the operator has to plan an investment, in order to increase the capacity of the network. User Satisfaction: This is an exponential ponderation coefficient of the operator gross profit. It takes into account the user being frustrated if his throughput is too low.

413

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Chapter XXVI

Telecommunication Investments Analysis: A Multi-Criteria Model Georgios N. Angelou University of Macedonia, Greece Anastasios A. Economides University of Macedonia, Greece

Abstract Recognizing the inadequacy of traditional quantitative cost-benefits analysis for evaluating telecommunications investments, researchers suggest real options (ROs) for controlling and valuating telecommunications business activities. However, ROs are based on the concept to delay investment for collecting more information and learning more about business conditions and during this delay another competitor may act gaining significant competition advantage. In addition, RO models are strictly quantitative and very often telecommunications investments may contain qualitative factors, which cannot be quantified in monetary terms. In addition, ROs analysis results in some factors that can be treated more efficiently when taken qualitatively. This work deals with quantitative and qualitative analysis and integrates ROs and Analytic Hierarchy Process (AHP) into a common decision analysis framework providing a multicriteria model, for analyzing telecommunication investments in the deregulated business field.

Introduction Telecommunications markets all over the world recently have been, and still are, undergoing drastic changes, fuelled my market reforms and technological progress. State-owned monopolists have been privatized and markets have been liberalized. These transformed markets have attracted

entrants in many varieties. Some entrants roll out complete networks, while other build only partial networks or perhaps offer services without having infrastructure themselves but having access to the networks of incumbent operators. The valuation of telecommunication business activities is a challenging task because it is characterized by high-level uncertainty. In addi-

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Telecommunication Investments Analysis

tion, these business activities are not possessed exclusively by a single firm but rather are shared by many competitors. The main challenge for a potential provider (investor) is to roll out its business activity at the right time and the right scale. The time and scale depend on telecommunication services penetration, network infrastructure cost, area characteristics, applications offered, expected tariff evolution, customers’ willingness to pay, demand forecasts, evolution of expected market shares and investor’s technical skills. Although the traditional cost-benefit analysis expressed in money terms such as investment cost, revenues, and Net Present Value (NPV) are significant factors to be taken into account in the analysis process, it is by no means sufficient for capturing the complexity of the problem in its entire. It is not able to accommodate the flexibility, for example, to defer and to abandon an investment plan at certain discrete pre-specified points in time. Real Options (ROs) address this inadequacy and offers management the flexibility to take actions, which can change aspects of the business activity over time. ROs have been proposed for business analysis and risk management (Trigeorgis, 1996). ROs applications to risk management and investment evaluation of telecommunication business field have mainly focused on a single and a-priori known option. However, these options are not inherent in any telecommunication investment. Actually, they must be carefully planned and intentionally embedded in the telecommunication investments in order to mitigate its risks and increase its return. Moreover, when a telecommunication investment involves multiple risks, by adopting different series of cascading options we may achieve risk mitigation and enhance investment performance. Given the investment’s requirements, assumptions and risks, the goal is to maximize the investment’s value by identifying a good way to structure it using carefully chosen real options (Benaroch, 2002).

However, ROs application in telecommunication business field raise some issues that require attention. ROs models are strictly quantitative, while telecommunication analysis may also involve qualitative factors. In addition, ROs analysis itself brings to the “surface” a number of factors that cannot be quantified, at least easily, by existing ROs models and methodologies. In this work we discuss all these issues and include them in a multi-criteria perspective providing specific decision analysis models. We consider that a holistic methodology is required in order to assist executives and decision makers in formulating problem parameters, understanding their interactions, estimating their contribution to the overall business value and so valuating effectively new telecommunication business activities. We discuss limitations of the quantitative analysis, in the specific field proposing qualitative factors that can be combined in a multi-criteria analysis. For integrating quantitative and qualitative factors in one utility function we adopt Analytic Hierarchy Process (AHP). The proposed analysis provides a better understanding of the telecommunication risks and the various qualitative factors inherent in such investments, enabling these investments to be deployed more optimum and valued with higher accuracy. Our main contributions are the following: •

•

We integrate financial quantitative, qualitative and risk factors as provided by the ROs and competition threat in an Analytic Hierarchy Process (AHP) structure. We provide a risk management framework for telecommunication investments based on ROs thinking.

Our aim is to find the business deployment that achieves a balance between risk control and performance maximization under competition. The rest of the paper is organized as follows. In Section 2, we provide background for the involved

415

Telecommunication Investments Analysis

techniques. In Section 3, we provide the proposed methodology and model. In Section 4, we apply the proposed decision analysis framework to a real life case study. In Sections 5 and 6 we conclude and suggest possible future research.

Background ROs Background Material An option gives its holder the right, but not the obligation, to buy (call option) or sell (put option) an underlying asset in the future. Financial options are options on financial assets (e.g. an option to buy 100 shares of Nokia at the pre-agreed price 90€ per share on January 2008). ROs approach is the extension of the options concept to real assets (Trigeorgis, 1996). For example, a telecommunication investment can be viewed as an option to exchange the cost of the specific investment for the benefits resulting from this investment. An investment embeds a RO when it offers to the management the opportunity to take some future action (such as abandoning, deferring or expanding the investment) in response to events occurring within the firm and its business environment (Trigeorgis, 1996). Telecommunication research on ROs recognizes that such investments can embed various types of ROs, including: defer, stage, explore, alter operating scale, abandon, lease, outsource, and growth. Trigeorgis (1996) provided an in-depth review and examples on different real options. For more practical issues the reader is referred to Mun (2002). Especially, for the telecommunication business field Iatropoulos et. al. (2004) applied ROs analysis for analyzing broadband technology investments. Finally, Angelou and Economides (2005) provided an extended survey of ROs applications in real life telecommunication investments.

416

Real Options Limitations and Need for Qualitative Perspective Integration In business practice, several conceptual and practical issues emerge when trying to use options theory as proposed in the current information communication technology (ICT) literature. It is accepted that all ROs models provide approximate valuations of ROs values (Renkema, 1999). Even the so-called accurate ROs models such as the Black-Scholes formula require some assumptions whose validity is still under criticism in the field of telecommunication investments. In particular, while ROs analysis is widely proposed for evaluating such investments, it is still accepted that ROs applicability is limited by the fact that ICT investments assets are not traded. The non-tradability of ICT assets cannot reveal the investor’s risk attitudes to estimate the correct discount factor of ICT investments. The theoretical foundation of the ROs analysis and its relevance to ICT investments has been discussed and applied in practice by Benaroch and Kauffman (1999, 2000) as far as the real asset non-tradability issue and risk-neutrality of the investor are concerned. However, its limitation is still under discussion. Existing models for ROs valuation assume a certain distribution of the resulting cash flows, based on an efficient market. However, this is rarely the case in the context of investments in the ICT business field, which is known for its uncertain and unpredictable conditions. It has also been recognized that finance-oriented option valuation models are too complex for managerial decision-making practice, when real life business conditions are considered Fichman et. al. (2005). In particular, after the liberalization of the telecommunication market, the required competition modeling has increased the complexity of existing options models. It is very difficult for senior managers to accurately estimate the parameters of a statistical distribution of outcomes and mainly volatility since they do not really have a “gut feel”

Telecommunication Investments Analysis

for the estimation of the volatility, even though they understand its technical definition as a statistic. Options theory in its present state does provide a conceptual decision framework to evaluate technology investments but, in many cases, cannot be considered as a fully operational tool for management. If it is expected that practitioners and senior managers will resist the use of formal options pricing models, then the qualitative option valuation can be an alternative analysis process. This is based more on the intuition of decision makers and forecasting for risks profiles, and less on sharply quantified prediction for parameters used in the formal options models. Overall, these issues suggest that even quantified ROs analysis could produce only approximate valuations, which in some cases can cause serious mistakes in investment decisions (Fichman et. al., 2005). For these reasons, we may adopt typical DCF techniques such as NPV instead of ENPV value and combine tangible factors with qualitative ROs thinking. Hence, our multi-criteria decision analysis framework can be extended including typical tangible factors from financial perspective and intangible ones from qualitative ROs thinking.

can be easily transformed into a single utility measure. As input, AHP uses the judgments of the decision makers about the alternatives, evaluation criteria, relationships between the criteria (importance), and the relationships between the alternatives (preference). In the evaluation process, subjective values, personal knowledge, and objective information can be linked together. As an output, the goal hierarchy, the priorities of alternatives and their sensitivities are reached. Concerning, examples of AHP application in information, communication technology literature, Bodin et al. (2005) proposed the AHP method to determine the optimal allocation of a budget for maintaining and enhancing the security of an organization’s information system. Hallikainen et al. (2002) proposed an AHP-based framework for the evaluation of strategic IT investments. They applied the principles of AHP to compare a number of Information Technology investment alternatives. Tam and Tummala (2002) formulated and applied an AHP-based model for selecting a vendor for a telecommunications system. Lai et al. (1999) applied the AHP to the selection of a multimedia authoring system. Finally, Kim (1998) used the AHP to measure the relative importance of Intranet functions for a virtual organization.

A Brief AHP presentation and Literature Review AHP is a multi-criteria decision analysis technique. It aims at choosing from a number of alternatives based on how well these alternatives rate against a chosen set of qualitative as well as quantitative criteria Saaty and Vargas (1994), (Schniederjans,2005). Using AHP, it is possible to structure the decision problem into a hierarchy that reflects the values, goals, objectives, and desires of the decision-makers. Thus, AHP fits the strategic investments problems and the framework of this study. The main advantage of the AHP approach is that different criteria with different measures

The proposed model-methodology Next, we present a methodology that helps to address the question: How can we control firm, market and competition risks so as to configure a specific telecommunication business activity in a way to minimize risk and increase performance? The proposed model contains three perspectives, financial tangible factors (FTF) perspective, risk mitigation factors (RMF) perspective, and intangible factors (IF) perspective (Figure 1).

417

Telecommunication Investments Analysis

Figure 1. The proposed model – three perspectives Financial Tangible Factors Perspective

Company Business Planning Risk Mitigation Factors Perspective

Intangible Factors Perspective

Financial Tangible Factors Perspective The financial perspective evaluates how a company is meeting though financial measures. For the valuation of financial perspective we may adopt traditional accounting techniques such as Net Present Value (NPV), Return on Investment (ROI) and Internal Rate of Return (IIR). We also include the Expanded Net Present Value (ENPV), which is the business value as estimated by ROs analysis. As mentioned before in the deregulated business field typical ROs models do not sufficiently model the competition threat. We propose the model of Angelou and Economides (2007B) for estimating the business value with ROs under competitive conditions in a business environment with may players. They adopt exogenous competition modeling considering that competitors’ arrival rate and competition impact from each entry into the market follow a joint-diffusion process with business revenues.

Intangible Factors (IF) Perspective Intangible factors are difficult, if not impossible, to quantify in absolute monetary terms, but are still important to the decision making process. Particularly, ROs analysis itself brings to the

418

“surface” a number of factors that cannot be quantified, at least easily, by existing ROs models and methodologies. Fichman et al. (2005) called them potential pitfalls of option thinking for risk management and investment evaluation. We integrated some of them, in our analysis, in order to achieve a balance between risk control achieved by options adoption and other issues influencing the overall investment’s deployment strategy and limit the options thinking applicability. Among others, not all investments can be divided into stages implementing stage and expand options. Sometimes a firm should consider an investment as a whole entity, such as when external funds must be raised or when co-investment from other parties is required. Another issue is that stakeholders may prefer all at once funding to obtain maximum control of the investment and have so more time to get a troubled investment back on track before facing a next track of justification. We introduce this possibility in our analysis by considering the intangible factor “CapabilityInterest of staging the investment” (CSI). In ROs literature investment opportunities, known in advance, based on initial infrastructure investments are treated as growth options, while for the estimation of their values compound option models are utilized. However, telecommunication growth investment opportunities in reality can be hardly defined during decision phase (Benaroch, 2002). For this reason, we model qualitatively the existence of growth investment opportunities, which are based on investments in previous phases of a firm’s business activity and cannot be defined quantitatively in advance. Concerning growth options, the main challenge is the difficulty of estimating their values (due to ambiguity of future cash flows) and uncertainty about the appropriate value for option model parameters. We name this intangible option factor as “no clarified growth options” (NCO). Also, building in option to abandon or contract operation may concern intangible costs related to credibility and morale. We model this

Telecommunication Investments Analysis

possibility by the intangible factor “cost of scaling down operation” (CSO). Finally, a potential pitfall of switch-use option is that it can add extra time and expense to the development of the initial information communication technology platform in order to change from shadow to real option. Creating this option (making it real) usually involves making the ICT platform more generic and modular for obtaining higher flexibility, experiencing however higher cost. We model this issue as intangible factor named “cost of systems flexibility-modularity” (CSF). Another factor that can be integrated in a future work is the higher uncertainty clearnesscontrol (UC) during waiting period. In our model, we consider the amount and type of uncertainty control achieved by each of the portfolio’s projects. We do not want to substitute the UC, achieved by the ROs analysis and quantified by the volatility of the stochastic parameters, such as investment revenues V and one time investment cost C (σv, σc). However, the overall uncertainty of an investment opportunity cannot be easily quantified. For example, the uncertainty of customers’ demand may be quantified by estimating its contribution in the overall investment’s volatility, while the contribution of technology and the firm’s uncertain capability to optimally exploit investment benefits may not. By adopting qualitative analysis, we can model some of the uncertainties inherent in the investment opportunity that cannot be quantitatively estimated and included in the overall investment’s volatility. Benaroch (2002) provided a method for estimating the overall investment’s uncertainty (volatility), which can be broken down into its components (e.g., customers’ demand uncertainty, competition’s uncertainty and technology’s uncertainty). However, the estimation of each component of the uncertainty may be impossible. We may extend this work by considering that some of the overall components of the uncertainty may be treated as qualitative factors, while the sources of uncertainty that can be quantified and included

in the estimation of the overall volatility can be integrated into the typical ROs models. Angelou and Economides (2008) provide an extensive discussion of these subjects.

Risk Mitigation Factors Perspective Risk management strategies are oriented towards identifying different types of risks, assessing their relative importance for the project, and implementing strategies for managing risks (Kumar, 2002). Risk management actions can be viewed as being of two types. The first is oriented towards reducing the degree of risk; for example, a major source of uncertainty in IT projects is uncertainty regarding the scope or specifications of the project. This can be partially resolved by interviewing multiple stakeholders. However, since risk cannot be completely eliminated, a second type of strategy, oriented towards hedging risks is important. Risk hedging strategies are insurance-like ones oriented towards minimizing the negative impact of risk, when the associated uncertainty is resolved over time. For example, specification uncertainty in IT projects may be due to uncertain business conditions that may be resolved as the project progresses (Kumar, 2002). Telecommunication risks can be placed into three categories (Benaroch, 2002; Bräutigam and Esche, 2002). •

•

Firm-specific risks are due to uncertain endogenous factors (endogenous or technical uncertainty). They could be the result of uncertainty about the ability of the firm to fully fund a long-term capital-intensive investment, the adequacy of the firm’s development capabilities to a target investment, the fit of the target application with various organizational units, etc. These factors affect the ability of the investing firm to successfully realize an investment opportunity. Competition risks are the result of uncertainty about whether a competitor will make a preemptive move, or simply copy the 419

Telecommunication Investments Analysis

•

investment and improve on it. These risks give rise to the possibility that the investing firm might loss part or all of the investment opportunity. Market risks are due to uncertain exogenous factors that affect every firm considering the same investment (exogenous or market-related uncertainty). These risks could be the result of uncertainty about customer demand and prices for the products or services, a target investment yields, potential regulatory changes, unproven capabilities of a target technology, the emergence of a cheaper or superior substitute technology, and so on. These factors can affect the ability of the investing firm to obtain the payoffs expected from a realized investment opportunity.

Research on technology investment’s evaluation and risk management recognizes that ROs thinking emphasizes the sources of risks inherent in such investments and contributes to risk control.

Life-Cycle of Investment Opportunity Real Options The lifecycle of an investment starts at the inception stage. During this period the investment exists

as an implicit opportunity for the firm that can be facilitated by a prerequisite investment (Figure 2). The firm possesses a shadow option. During the recognition stage, call “Wait-and-See” (WaS) period, the investment is seen to be a viable opportunity. The opportunity can be treated as a RO. The building stage follows upon a decision to undertake the investment opportunity. In the operation stage, the investment produces direct and measurable payoffs. Upon retirement, the investment continues to produce indirect payoffs, in the form of spawned investment opportunities that build on the technological assets and capabilities it has yielded. When these assets and capabilities no longer can be reused, the investment reaches the obsoleteness stage. Each stage of the investment opportunity is relevant to a number of operating and growth ROs, such as option to defer, stage, lease, expand (Benaroch, 2002). The reason is that each type of RO essentially enables the deployment of specific responses to threats and/or enhancement steps. In addition, each stage of the investment is also experiencing a variety of risks. For controlling these risks we can adopt a number of investment modes Defer investment to learn about risk in the investment recognition stage. If we don’t know how serious some risk is, the option to defer investment permits learning about the risk by acquiring

Figure 2. Types of risks and ROs arising at different stages in the investment lifecycle Inception stage

Recognition stage

Operation stage

Types of risks

Competition Market

Competition, Market, Organizational

Competition, Market, Organizational

Competition, Market

Existence form

Shadow investment opportunity Shadow option

Real investment opportunity

Opportunity realization

Strategic Growth /Operating option Option t o Defer investment

Operating Option

Operation of implemented opportunity Operating option

Stage, p ilot, lease and outsource options

Contract, expand, outsource, abandon operations options

Source of value Type of RO

Prerequisite investments

420

Building stage

Retirement Obsoleteness stage stage

Future (spawned) investment opportunities

Telecommunication Investments Analysis

information passively (observe competitor moves, review emerging ITs, monitor regulatory actions, etc.) or actively (conduct market surveys, lobby for regulatory changes, etc.). Such learning-by-waiting helps to resolve market risk, competition risk, and organizational risk. Apparently, the greater the risk, the more learning can take place, and the more valuable is the deferral option. Partial investment with active risk exploration in the building stage. If we don’t know how serious some risk is, investing on a smaller scale permits to actively explore it. Three options facilitate learning-by-doing, that is, enable gathering information about the firm’s technological and organizational ability to realize the investment successfully. The option to stage investment supports learning via a sequential development effort, and the options to pilot and prototype support learning through the production of a scaled down operational investment. The last two options compress the investment lifecycle, thus allowing to learn early how competitors, customers, regulatory bodies and internal parties will react to the investment initiative. Put another way, these options permit market risk, development risk and organizational risk to be transferred to earlier parts of the full scaled investment lifecycle. Similarly, the stage option divides the investment realization effort into parts, thus permitting to transfer risk across parts within the building stage. For example, implementing the riskiest parts of the realization effort as early as possible helps to reveal up-front whether the entire realization effort can be completed successfully (e.g., within schedule and budget). Full investment with reduction of the expected monetary impact of risk in the building and operation stages. Here, options help to lower the value consequences of risk and/or the probability of its occurrence. An example of the former is the option to lease development resources, which protects against development and market risks by

allowing to kill an investment in midstream and save the residual cost of investment resources. A way to lower the probability of risk occurrence is the option to outsource development. This option lowers the risk of development failure by subcontracting (part or all of) the realization effort to a third party that has the necessary development capabilities and experience. In essence, both these options permit transferring risk (partially or fully) to a third party. Dis-investment/Re-investment with risk avoidance in the operation stage. If we accept the fact that some risk cannot be actively controlled, two options offer contingency plans for the case it will occur. The option to abandon operations allows redirecting resources if competition, market or organizational risks materialize. The option to alter scale allows contracting (partially disinvest) or expanding (reinvest) the operational investment in response to unfolding market and organizational uncertainties. Based on the logic of these investment modes, the mapping of specific risks to specific options that control them can be refined to fit any class of IT investments. Examples of ROs thinking in the basis of the aforementioned investment modes are provided by Benaroch (2002) and Angelou and Economides (2007 A). Particularly, they apply ROs thinking based on the aforementioned investment modes for analyzing information technology investment opportunities. ROs analysis can control different sources of risks existing in the various stages of the investment life-cycle. We use a classification for analytical definition of telecommunication risks based on Benaroch (2002) and (Bräutigam & Esche 2002) proposals. Table 1 shows the main sources of telecommunication risks as well as their mapping to the specific ROs that can control them. In the following we propose an AHP structure in order to combine all the aforementioned factors into one utility function.

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Telecommunication Investments Analysis

Table 1. Risk factors inherent in telecommunication investments and options that can control them Risk Opportunity

Recognition Defer

Building Stage

Explore/Pilot

Operation

Outsource Lease Abandon Contract Expand Outsource Development

F1

+

+

+

F2

+

+

+

+

P1

+

+

+

+

+

P2 project is too large or too complex

+

+

+

+

P3 inadequate infrastructure for implementation

+

+

P4 the project is not on Time

+

+

F1 wrong design (eg, analysis failed to assess correct requirements)

+

+

F2 problematic requirements (stability, completeness, etc.)

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

O1 uncooperative internal parties

+

O2 parties slow to adopt the application C1

+

C2

+

E1 low customer demand, with inability to pull out of market

+

E2 demand exceeds expectations (follow-up opportunities exist)

+

+

E3 too high customer response may overwhelm the application

+

+

E4 customers may (bypass) develop their own solutions

+

+

E5 unanticipated action of regulatory bodies

+

E6 Price uncertainty

+

E7

+

+

+ +

+

+

+

+

+ + +

+ +

+

+

+

+

+

+ +

+

+

E8 Other factors such as Legal issues, Natural Phenomena, Social +

+ +

T1 application may be infeasible with the technologies considered T2 the introduction of a new superior implementation technology may render the application obsolete

+

T3 the implementation technologies considered may be immature

+

Integrating qualitative Real Options with AHP model The structure of the decision analysis framework contains four levels: i) the content of the specific investment opportunity, which can be deployed in various ways, ii) the life-cycle stages of the investment opportunity, iii) the options level that is embedded in each of these stages and mapped to specific types of risks, iv) the multi-criteria level that contains financial tangible, risk and intangible analysis (Figure 3). The overall utility of AHP structure is composed by these criteria (factors), which may be further decomposed into their applicable sub-criteria. We apply the pairwise comparisons for each of these sub-criteria. The final result of the analysis, at the top, is the prioritization of the various deployment scenarios according to the overall firm business utility.

422

+

+

+

+

+

+

+

+ +

The analytical view of the Risk Mitigation submodule is deeply analyzed in Figure 4. The criteria used in our structure are coming from Table 1 and indicate the risk inherent in telecommunication investments. Analytically, we perform pair-wise comparisons of the deployment scenarios for each of the risk factors focusing on the risk control that each scenario can provide. The pair-wise comparisons concern the amount of risk that is resolved and controlled, depending on the option(s) existence in each scenario. Our target is to select the deployment scenario that provides the highest value for the risk mitigation utility.

Summary The proposed methodology involves four main steps that must be repeated over time as more information is collected concerning the overall business environment. These steps help to opti-

Telecommunication Investments Analysis

Figure 3. Analytical view of the decision analysis framework Business Utility

Financial Tangible Factors

Intangible Factors

Risk Mitigation Factors -

Net Present Value

CSI

…It is analyzed extensively... infigure 4

ENPV

NCO CSO

Payback Period

CSF Investment Costs

Defer

Stage

Explore/ Pilot

Outsource development

Recognition

Deployment Scenario 1

Abandon

Contract

Building

Deployment Scenario 2

mally configure the investment under the information set available initially, but as time passes they must be re-applied in case that some risks get resolved or new risks surface. In the following we present these steps. • Define the content of the overall business activity and its risk profile. State the investment goals, requirements and assumptions (technological, organizational, economic, etc.), and then identify the risks inherent in the investment. • Recognize the options mapped to specific risks and use them to adopt investment modes to be examined.

Expand

Outsource Operation

Operation

Deployment Scenario …

Deployment Scenario N

• Evaluate investment-structuring alternatives and find a subset of the recognized options that maximally contributes to the investment value. For the evaluation of the structuring alternatives we use AHP analysis and perform pair-wise comparison among the alternatives. For the AHP implementation we adopt the commercial tool Expert Choice. • Perform sensitivity analysis in order to understand the contribution of each criterion in the overall business utility.

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Figure 4. The risk mitigation sub-module of the proposed framework Risk Mitigation Utility

Firm Specific Risks F1

E1

F1

F2

E2

F2

P1

E3

P2

E4

P1

E5

P3

E6

P4

E7

F1

E8

F2

T1

O1

T2

O2

T3

Stage

Defer

Explore/ Pilot

Outsource development

Deployment Scenario 1

Abandon

Contract

Building

Recognition

Deployment Scenario 2

A Case Illustration To illustrate the proposed methodology we apply it to an ICT investment decision for a growing Water Supply & Sewerage Company, which we refer to as WSSC to protect its identity and its projects. We focus on the risk mitigation factors. The Company’s principal business is the supply of water and sewerage services to over 1.5 million people. The WSSC is challenged on several areas. First, there is an opportunity for the WSSC to offer advanced water management services to its existing customers. This results to enhanced

424

Competition Risks

Market Risks

Expand

Outsource Operation

Operation

Deployment Scenario …

Deployment Scenario N

service quality and efficient control of its operating expenses. In addition, its service area is going to significantly increase attracting new customers. In order to achieve all these WSSC management is focusing on the significance of the ICT applications that could transform the company’s relationships with customers, suppliers, other partners and environment regulators. WSSC is interested in proceeding on implementation of an ICT platform in order to improve automation aspects of its operations, decision taken methods, customer services as well as new strategic opportunities in long-term perspective.

Telecommunication Investments Analysis

A.

Define the Content of the Overall ICT Business Activity and its Risk Profile

•

Analytically, the investment opportunity under examination includes.

•

•

Telemetry-ICT (TICT) infrastructure to enable WSSC to perform more efficiently water network management as well as Asset Management.

Of course, the system integration with the functional internal processes of the company requires re-engineering of the company’s internal processes and especially these that are related to the customer support and information. In our analysis we consider the aforementioned investment opportunity as an overall entity. We focus on Risk Mitigation Factors Perspective.

WSSC also examines the possibility of integrating two extra tools into the ICT platform for improving the decision support processes: •

StruMap, a Hydraulic Analysis simulation tool, which helps the Water Network Modeling and therefore the Water Management. Finally, based on the information collected and manipulated by the afore mentioned platform and its sub-modules a web-based customers support tool will be implemented providing also on line question and answer service to WSSC customers.

ArcInfo, a Geographical Information System (GIS), that allows users to create, view, access and analyze map (geo-referenced) data.

Figure 5. A configuration of options taken into account in our analysis R ec ognition s tage B uilding s tage defer investment partial or full mode investment mode

0

1

2

3

O peration s tage re-investment or/and dis-investment mode

5

I

6

15

outsource

tim e

stage 2

expand 1 contract expand 2

stage 1 defer

Defer: To defer (up to Td=2years) the base scale TICT platform that contains the Telemetry-ICT system for water management monitoring system including the asset management module (D). Stage: To build ICTP base scale platform in two stages at Ts1=Td and Ts2=Td+1 option to stage 1 (S1) and option to stage 2 (S2). The option to stage S1 concerns the pure telemetry system while the options to stage S2 concerns the asset management sub-module. Expand: We consider the option to expand (E1) operation at Te1= Td+2 as well as the option to expand (E2) at Te2=Td+3. The first option to expand concerns the GIS and HM sub-modules integration with the Telemetry-ICT base scale system, while the second option the development of a new web-based customers support tool that is based on the technical information retrieved by the already installed and operated sub modules of the ICTP system. Contract: The company’s management may also decide to contract operation for investment stage (E1) instead of expanding them to E2 web-based customer support tool if business conditions become unfavorable. Outsource: The company’s management examines the possibility of outsourcing the base scale operation and maintenance of the T-ICT system after 4 years of operation (i.e. at To=Td+4)

425

Telecommunication Investments Analysis

Finally, there is uncertainty about the firm’s capability to integrate efficiently the initially planned scale of the ICT infrastructure with the required applications as well as with the content of them.

The investment goals, requirements, assumptions and risks are summarized as follows.

Risks Presentation Concerning the specific investment opportunity for the WSSC there are some risks that can influence negatively its performance. In our case, there are mainly company-specific risks, environmental and technological risk since the Company does not experience any customers demand uncertainty or any competition threat. In particular, many of the ICT investments projects either completely fail, or deliver reduced functionality. ICT platform may experience lack of users acceptance, but also lack of companies personnel technical expertise. Also, risk factors may concern unrealistic implementation schedule and environmental complexities such as installation of complex equipment in a large scale that can cause inconvenience to the customers. Risks modeling included in our analysis is given in gray cell in Table 1.

B.

Recognize the options mapped to specific risks and use them to adopt investment modes to be examined.

In this step recognize the options that the investments could embed, based on the identified investment risks. The overall investment deployment strategy in its most complex strategy can include all the options that can control partially or fully the specific investment’s risks, Figure 5. In our analysis we consider the options to defer, stage, expand, contract and outsource operations. The investment’s deployment scenarios to be examined are seen in Figure 6. We are looking for the optimum ranking of these scenarios.

Figure 6. Scenarios examined (options combinations – investment content) Scenario 1 – Full investment/Dis-investment mode O: WB or C:WB Stage 2 at t=2

T-ICT+AM+GIS+HM+WB Stage 1 at t=0

O: T-ICT Stage 3 at t=3

Scenario 2 –Partial investment / Re-investment/Dis-investment mode S1: T-ICT Stage 1 at t=0

S2: T-ICT+AM Stage 2 at t=1

E1-E2: T-ICT+AM+GIS+HM+WB Stage 3 at t= 2

O: T-ICT and/or C:WB Stage 4 at t=3

Scenario 3 – Defer investment / Dis-investment mode O: T-ICT and/or C:WB Stage 2 at t=Td+2

D: T-ICT+AM+GIS+HM+WB Stage 1 at t=Td

Scenario 4 – Defer investment / Re-investment/Dis-investment mode D-S1-S2: T-ICT+AM Stage 1 at t=Td

E1-E2: T-ICT+AM+GIS+HM+WB Stage 2 at t=Td+1

O: T-ICT Stage 3 at t=Td+2

Scenario 5 – Defer investment / Re-investment/Dis-investment mode D-S1-S2: T-ICT+AM Stage 1 at t=Td

E1: T-ICT+AM+GIS+HM Stage 2 at t=Td+1

E2: T-ICT+AM+GIS+HM+WB Stage 3 at t=Td+2

O: T-ICT Stage 4 at t=Td+3

Scenario 6 – Defer investment / Partial investment / Re-investment/Dis-investment mode D-S1: T-ICT Stage 1 at t=Td

S2: T-ICT+AM Stage 2 at t=Td+1

E1: T-ICT+AM+GIS+HM Stage 3 at t=Td+2

The different boxes indicate different investment stages ( --- recognition and building stages, operation stages )

426

E2: T-ICT+AM+GIS+HM+WB Stage 4 at t=Td+3

O: T-ICT Stage 5 at t=Td+4

Telecommunication Investments Analysis

C. Evaluate investment-structuring alternatives (investment modes) and find a subset of the recognized options that maximally contributes to the investment value We have identified the alternative ways to configure the ICT investment using different subsets of the recognized options. For the evaluation of the investment alternatives we do not adopt the quantitative analysis and existing ROs models such as Black-Scholes formula or binomial model. Our intentions was also supported by the interview process with the company’s management, which revealed the degree of uncertainty for the various phases of the investment. The company’s management expressed the uncertainties level for each investment phase in qualitative way, since it had difficulties in expressing the volatility of the expected value of investments benefits. Applying the proposed AHP methodology, the pair wise comparison matrices are derived and the relative performance measures are computed for intangible risk factors. We use the nine-point scale as suggested by Saaty et. el. (1994) however, modified in order to incorporate with our analysis. In particular, we judge our projects portfolio as extreme risk control (E), very strong risk control (VS), strong risk control (S), moderate risk control (M) and

equal risk control (E) including intermediate values between the main characterization types. By using the Expert Choice and making judgments according the aforementioned nine-point scale we derive the pair wise comparison matrixes. Our example is for intuition purpose only and hence we do the scoring alone. Roper-Lowe and Sharp (1990) comment that since it is sometimes difficult to find technical people who can compare options it is necessary for the analyst to learn in detail about each option and do the scoring alone. We play here the analyst role. We select the consistency ratio level, as according to AHP method a consistency ratio must be less than 0.10 to be acceptable (Saaty, 1994). After making all paired comparisons, for all alternatives, according to the principles of the AHP with respect to all criteria defined in the proposed framework, we compute the total priorities for the alternatives using the known commercial tool Expert Choice. The prioritization results are given in Figure 7. As it can be seen higher risk mitigation utility value is given by scenario 6 and scenario 5 is following. However, though more option may generate higher control risks in general the financial tangible and intangible factors contribution may change the aforementioned conclusion.

Figure 7. Scenarios prioritization performed with Expert Choice tool Model Name: Risk M itigation Ut ility-ROs-AHP_PCI2007 Synthesis: S ummary

synthesis with respect to: risk mitigation utility O verall Inconsistency = ,06 sc1 sc2 sc3 sc4 sc5 sc6

,050 ,171 ,103 ,113 ,178 ,385

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Telecommunication Investments Analysis

Figure 8. Sensitivity analysis for firm specific risks Gradient Sensitivity for nodes below: Risk Mitigation Utility

,40

Alt% Sc6

,30

,20

Sc2 Sc5 Sc3 Sc4

,10

Sc1 ,00

0

.1

.2

.3

.4

.5 Fir m Risk s

D. Sensitivity analysis Performing sensitivity analysis we can study how sensitive the priorities of the alternatives are to the changes of the input data, i.e. the importance of the criteria. Figure 8 shows the sensitivity analysis of the results with respect to the importance of firm risk factors. The figure shows that scenario 6 experiences the highest utility value. Also, for firm risk factors weights from 0 up to 0,75 scenario 5 presents the second priority, while from 0,75 to 1 scenario 2 becomes the second best. The input data are quite subjective, especially the intangible ones. For this reason, it is important to study the dynamics of the sensitivities carefully. For example, if the importance of one criterion changes significantly, the priorities of between scenarios may change due to space limitations we do not present these results while they are available to the interest reader.

428

.6

.7

.8

.9

1

5. Discussion and Future Trends There is empirical evidence to support the fact that managers who are aware of some options-like ideas do a better job of evaluating and managing risky telecommunication investments. Also, senior finance executives are becoming increasingly aware of the need to view major risky capital investments as options. ROs have already applied in the literature for risk management and evaluation of telecommunication investments. In practice managers identify risks and formulate strategies that can control these risks in the most efficient way. These strategies may contain option analysis and the target is to map options to risks and find the optimum combination of them in order to achieve the optimal value for the investment opportunity. However, the option analysis experiences criticism concerning the need for the parameters quantification of the option models. The issue becomes even more complicated

Telecommunication Investments Analysis

in telecommunication markets. Particularly, after the markets liberalization competition intensity has been increased dramatically and the players are usually so many that oligopoly models are becoming very complicated to be used in practice. Hence, the quantitative analysis of competition influence in telecom investment opportunities is a very difficult task that requires high-level of mathematical modeling and high number of assumptions while managers and practisians quite often do not “feel comfortable” to adopt it. Instead, we provide qualitative option thinking. Our analysis requires from the management and business analysts to recognize qualitatively the options, during the lifecycle of an investment opportunity that can at least partially control specific risks. Sometimes deferring an investment may be optimum, while some other times the immediate implementation is the best solution adopting afterwards a step-wise deployment strategy during building and operation period. We propose a decision analysis framework where we compare the various types of adopted options and investment modes for a telecommunication opportunity by adopting AHP analysis. In our analysis, we are not only based on qualitative option thinking but also integrate financial tangible and intangible factors coming by both the nature of the telecommunication investments and the options analysis itself. Our framework of analysis can be also applied in information technology (IT) service management (e.g. ITIL) and IT governance (e.g. Cobit). Particularly, they deal with issues such as how to provide a good service at the good price. People combine these approaches to the maturity concept. For example, risks P1 to P4 mainly depend on the maturity of the firm on the technologies used in the project, on its current infrastructure which indicates how the project will be integrated. IT service management and IT Governance frameworks are not mutually exclusive and could be combined to provide a powerful IT governance, control and best-practice in IT service management, (Mingay

and Bittinger, 2002). Indeed, one can map ITIL process onto the perspective of the standard IT Balanced Scorecard (BSC) as follows. IT BSC Business Contribution Financial Management • IT BSC User Orientation • Service Level Management • Availability Management • Continuity Management • Incident Management • Financial Management IT BSC Operational Excellence • Problem Management • Service Level Management • Change Management • Service Level Management IT BSC Future Orientation • Service Level Management • Capacity Management • Change Management • Financial Management A similar mapping exists for the CobiT processes. For instance, in the delivery and support domain such as define and manage service levels, manage performance and capacity, ensure continuous service, etc. maps well onto one or more ITIL processes such as service level, configuration, capacity, availability management etc. (Salle, 2004). Similar to this analysis the aforementioned perspective can be applied to our model considering an AHP hierarchical structure.

6. Conclusion In this work we provide a decision analysis framework for prioritizing telecommunication investment deployment strategies adopting qualitative

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option thinking. In our analysis, we take into account financial tangible and intangible factors and quantify managerial flexibility in the projects’ implementation strategy. So far in the literature, ROs models employ only a quantitative factors analysis for both benefits and costs. However, very often a telecom ICT project also owns a number of qualitative factors that should be taken into account in parallel with the quantitative ones. In addition, the ROs analysis itself in existing models requires input parameters that very often are difficult to be fully quantified. For this reason, we adopt the AHP in order to structure risk profile for telecommunication investments and recognize options that can optimally control them as well as combine tangible and intangible factors into one utility function. It is the first time in the literature where ROs and AHP are combined in a common framework of analysis offering a multi-criteria prioritization model that contains risk, intangible and tangible factors related to telecom business activities. A limitation of our work is the lack of competition modeling especially focusing on oligopoly cases. In this case, someone could adopt game theory and integrate it with our analysis. In particular, we can consider two players where each of them has to configure its investment in a way that is optimum for him taking also into account the decisions of the competitor.

References Angelou, G. N., & Economides, A. A. (2007A). E-learning investment risk management. Information Resource Management Journal, 20(4), 80-104, October-December. Angelou, G. N., & Economides, A. A. (2007B). A Real Options approach for prioritizing ICT business alternatives: A case study from Broadband Technology business field. Journal of the Operational Research Society. Forthcoming doi:10.1057/palgrave.jors.2602477.

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Angelou, G. N., & Economides, A. A. (2008). A decision analysis framework for prioritizing a portfolio of ICT infrastructure projects. IEEE Transactions on Engineering Management, 55 (3), 479-495. Angelou G., & Economides A. (2005). Flexible ICT investements analysis using real options. International Journal of Technology, Policy and Management, 5(2),146–166. Benaroch M. (2002). Managing information technology investment risk: a real options perspective. Journal of Management Information Systems, 19(2), 43-84. Benaroch, M., & Kauffman, R. J. (2000). Justifying electronic banking network expansion using real options analysis. MIS Quarterly, 24(2), 197–225. Benaroch, M., & Kauffman, R. J. (1999). A case for using real options pricing analysis to evaluate information technology project investments. Information Systems Research, 10(1), 70-86. Bodin L., Gordon L., & Loeb M. (2005). Evaluating information security investments using the analytic hierarchy process. Communications of the ACM, 48(2), 78-83.   Bräutigam, J., & Esche, C. (2003). Uncertainty as a key value driver of real options. 7th Annual Real Options Conference. Expert Choice (1995). Expert Choice for windows based on Analytic Hierarchy Process, Version 9, User Manual. Pittsburgh, PA. Fichman, R., Keil, M., & Tiwans, A. (2005). Beyond Valuation: “Option Thinking” in IT Project Management. California Management Review, 47(2), 74-95. Hallikainen, P., Kivijarvi, H., & Nurmimaki, K., (2002). Evaluating strategic IT investments: An assesment of investment alternatives for a web content management system. Proceedings

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of the 35th Hawaii International Conference on Systems Sciences. Gunasekaran, A., Love, E., Rahimi, F., & Miele, R. (2001). A model for investment justification in information technology projects. International Journal of Information Management, 21, 349364. Iatropoulos, A., Economides, A., & Angelou, G. (2004). Broadband investments analysis using real options methodology: A case study for Egnatia Odos S.A. Communications and Strategies, 55(3), 45-76. Kim J. (1998). Hierachical structure of intranet functions and their relative importance: Using the analytic hierarchy process for virtual organizations. Decision Support Systems, 23, 59-74. Lai, S., Trueblood, P., & Wong, K. (1999). Software Selection: a case study of the application of the analytic hierarchy process to the selection of multimedia authoring system. Information & Management, 36, 221-232. Mingay S., & Bittinger S. (2002). Combine CobiT and ITIL for Powerful IT Governance. In Research Note, TG-16-1849, Gartner. Mun, J. (2002). Real Options Analysis: Tools and techniques for valuing strategic investments and decisions. Finance: Wiley. Renkema, T. (1999). The IT value quest: how to capture the business value of IT-based infrastructure. John Wiley & Sons, Ltd. Roper-Lowe G, & Sharp J. (1990). Analytic hierarchy process and its application to an information technology decision. Journal of Operational Research Society, 42(1), 49-59. Saaty, T. L., & Vargas, L. G. (1994). Decision making in economic, political, social, and technological environments with the analytic hierarchy process. Pittsburgh: RWS Publications.

Sallé, M. (2004). IT Service Management and IT Governance: Review, Comparative Analysis and their Impact on Utility Computing. Trusted Systems Laboratory, HP Laboratories Palo Alto. Schniederjans, M., Hamaker, J., & Schniederjans ,A. (2005). Information technology investment – decision-making methodology. Singapore: World Scientific Publishing. Tam, M., & Tummala, R. (2001). An application of the AHP in vendor selection of a telecommunications system. Omega, 29, 171-182. Trigeorgis, L. (1996). Real options: managerial flexibility and strategy in resource allocation. Cambridge MA: The MIT Press.

Key Terms Analytic Hierarchy Process (AHP): A process that deals in a hierarchical structure a number of quantitative and qualitative criteria in one utility function. Business Utility: It is the overall utility of the under investigation business activity for the company. It contains both quantitative and qualitative factors. Deployment Scenario: The way the investment is deployed in terms of time and scale implementation. Expanded Net Present Value: It is the total value of a project that owns one or more options. It is given by: Expanded (Strategic) NPV = Static (Passive) NPV + Value of Options from Active Management. Investment Cost: The amount of money spent for the investment, investment expenditure required to exercise the option (cost of converting the investment opportunity into the option’s underlying asset, i.e. the operational project).

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Real Option: It is the extension of financial options concept to real assets.

may preempt the owner of the ROs and “steal” or abstract its value.

Real Option Under Competition Threat: The value of ROs when during waiting period before exercising it there is the threat that a competitor

Risk Management: The process of identifying different types of risks, assessing their relative importance for the project, and implementing strategies for managing risk.

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Chapter XXVII

A Business Planning Framework for WiMAX Applications Rebecca De Coster Brunel University, UK

Abstract Mobile networking refers to wireless technologies which provide communications between devices. Applications for mobile networking have a broad scope as they can be applied to many situations in either industrial or commercial sectors. The challenge for firms is to better match market-induced variability to the organizational issues and systems necessary for technological innovation. This chapter develops a business planning framework for mobile networking applications. This framework recognises the fluidity of the situation when trying to anticipate and model emerging wireless applications. The business planning framework outlined in this chapter is a generic model which can be used by companies to assess the business case for applications utilizing mobile networking technologies.

INTRODUCTION TO WIMAX APPLICATIONS IN THE MOBILE NETWORKING SECTOR WiMax is a wireless standard that was developed to provide a wireless alternative to cable and DSL for broadband access (WiMax-Forum, 2004). The focus here is assessing the potential business case for WiMAX applications in the mobile networking sector. Mobile networking refers to wireless

technologies which provide communications between devices, for example, a laptop maybe connected wirelessly to a printer via radio using the Bluetooth standard. The WiMAX standard allows for both point-to-point and point-to-multipoint configurations – the latter being suitable for mobile networking applications. Point-to-multipoint microwave networks have been previously deployed as proprietary networks (Vaughan-Nichols, 2004), until the development

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A Business Planning Framework for WiMAX Applications

of the Institute of Electrical and Electronics Engineers (IEEE) 802.16 set of standards known as WiMAX (Worldwide Interoperability for Microwave Access). These global standards improve matters in two ways: compatibility of components within a communications system and customer interface standards. The availability of global standards for mobile networking technologies enables high technology firms to focus resources on specific aspects of a WiMAX communication system.

The Business Case for WiMAX Applications The purpose of the chapter is to examine the forecasting elements for emerging broadband wireless access applications. The chapter examines the elements involved in deploying a new product or service to determine whether or not a business proposal will create value. Value management is an approach to management based on the principle that business decisions are based on the premise that “they must manage a firm’s resources with the ultimate objective of increasing the firm’s market value” (Hawawini and Viallet, 2007, p. 521).

The availability of global standards such as WiMAX is a means for achieving greater adoption. This has been shown with the Wi-Fi (wireless LAN) networking standard where high user adoption rates have been experienced within a relatively short time period. However, significant ROI (return on investment) is not yet clear for WiMAX (Koffman and Roman, 2002) as the network and equipment costs are still high. The breadth of factors which need to be addressed during business planning for broadband wireless access is shown in Table 1. The ROI components present in Table 1 illustrate the high infrastructure costs involved with investment in both core and access networks with Gunasekaran and Harmantzis (2005) quoting backhaul costs of T3 as $2000 per month and OC3 of $5000 per month. This chapter develops an approach to examining the business case for WiMAX applications and develops a business planning framework. The business planning framework outlined in this chapter is a generic model which can be used by companies to assess the business case for applications utilizing mobile networking technologies.

Table 1. ROI components for broadband wireless access ROI Components

Key Factors

Key Variables

Applications

Voice/ data/ Internet

Supporting interfaces

Subscription take-up rate

Market Potential

Demographics; capacity per subscriber

Pricing Package

Installation charges and monthly subscription charges

WiMAX billing/tariff structures

Spectrum Licence fees

National availability of spectrum

National regulatory situation

Planning costs

Radio planning; business case

Tower site acquisition; frequency allocation and environment (multi-path)

Equipment costs

Backhaul and base station costs

Network topology ; wireless access configuration

Deployment costs

Installation charges

Ease of interconnectivity

Operating costs

Upgrades; maintenance etc..

Equipment interoperability

Revenues

Costs

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KEY COMPONENTS OF THE BUSINESS PLANNING FRAMEWORK The business planning framework for mobile networking technologies which has been developed is shown in Figure 1. The framework comprises two sides which need to be in alignment. The left-hand side identifies the elements to assess the market potential of mobile networking applications. The right-hand side of the framework identifies the elements to assess the business case of mobile networking applications. This approach differs from other forecasting approaches by utilising an open-systems view of innovation management. This means that the business planning framework supports generic approaches to planning innovation for emerging broadband wireless applications. Each element within the framework is a generic one and does not constrain the other elements in terms of their structure. This framework recognises the fluidity of the situation when trying to anticipate and model next-generation wireless applications. Previously broadband wireless access was considered an alternate solution to broadband access offered via DSL or cable due to the prominence of the

established network operators providing local loop services. This does not take into account the drivers and market development for next-generation wireless applications. The key developments for users were identified as working assumptions for fourth-generation mobile project (Bria et al, 2001) including: telepresence (in place of meetings); information anywhere, anytime; intermachine communication; security and one-stop shopping. Many consumer electronic applications in the mobile networking sector arise due to user demands for the convenience of wireless connectivity. The business planning framework outlined in Figure 1 is a generic model which identifies key components by which business proposals can be examined and the potential value identified.

Key Components of Market Potential The business planning framework recognises that firms must assess market potential to maximise return on investment (ROI). This requires analysis of collected information concerning market structures and market offerings in a systematic manner. An approach to assessing the market potential for broadband access services is to focus on the different demographics and the WiMAX billing/tariff structures as illustrated by a couple of

Figure 1. The business planning framework for mobile networking technologies

INNOVATION APPLICATION

Business Case COLLABOR -ATIONS

SCENARIOS

INNOVATION OPPORTUNITIES

Alignment

SECTOR Industry Value Chain

Technology Innovation Appraisal

INNOVATION FORECASTS

INNOVATION MODELS

Market Potential

Alignment

COMPETITIVE STRATEGIES

COSTS

RESOURCES

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Table 2. Modelling the market potential of broadband wireless access Model Assumptions

Customers Customer capacity requirement

Residential Example: Low Usage

Residential Example: High Usage

Residential

Small office

2MB/s to 5MB/s

5MB/s to 10MB/s

Depends on allocated frequency and radio planning

Depends on allocated frequency and radio planning

Number of homes in area

Number of offices in area

Initial Take-up estimates

20%

30%

Target Population

30%

40%

Geographic coverage Customer density

example scenarios in Table 2. The models shown are extensions on existing models for broadband wireless access (Petkovic and De Coster, 2000) including capacities forecasted for fourth and fifth generation mobile systems (Ohmori et al, 2000 and Ghosh et al, 2005) rather than capacities currently reported (Ballon, 2007). Revenues are essentially based on subscription take-up rates multiplied by the pricing package. The nature of the customers will be the key variable as residential users will have very different requirements and pricing levels to corporate users. Hence, demographics are a key factor in determining the business viability of any telecoms network (Ballon, 2007). Pricing components of a broadband wireless access service usually comprise two elements (Petkovic and De Coster, 2000): installation charges and monthly subscription charges. The installation charges need to cover the logistical and personnel costs and may include equipment costs. The monthly subscription charges are likely to consist of a mix of flat-rate or packaged WiMAX billing/tariff structures depending on the type of customer.

Innovation Opportunities The successful commercialisation of products encompassing new technologies requires a high level of market sensing (Anderson and Narus,

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2004, p41). This refers to the ability of firms to anticipate the desires of customers and trends in markets. The fast moving high technology sector of mobile networking is one where establishing market sensing is not easy to do. Many of the protocols and standards are only recently established and are yet to be deployed in the marketplace, for example, mobile WiMAX could support data transfer at vehicular speeds (Vaughan-Nichols, 2004). Wi-Fi has been shown to be a cost-effective broadband wireless access solution for rural and remote areas (Zhang and Wolff, 2004). The success of Wi-Fi was explained by three factors (Galperin, 2005): 1. 2 3

Provides wireless access as well as for backhaul traffic; Widespread industry support for the standard and The lack of regulatory overhead.

The growth in diversity of mobile devices is yet to occur and includes Smartphones, PDAs, Portable Media Centers, retail point-of-sale systems, Global Positioning System-based devices and industrial robots. This increasing number of user devices are challenging to support as they each have different interface requirements. The end users are seeking to gain improved usability through wireless connectivity. WiMAX

A Business Planning Framework for WiMAX Applications

has been added to the list of approved 3G radio access technologies in the International Mobile Telecommunications 2000 (IMT-2000) standard as defined by the International Telecommunication Union (ITU). It is unclear how attractive the services offered by third-generation mobile (3G) networks will be compared to Wireless-LANs such as Wi-Fi (Lehr and McKnight, 2003). From the end-user’s perspective value for the end-user is the means to express in monetary terms the functionality or performance of a market offering in a given customer application (Anderson and Narus, 2004). For example, a home cordless base station will connect a mobile phone to the public telephone network in order to reduce cost of calls and remove the need for dedicated home wireless terminals as cordless phones. Consumer applications utilising wireless connectivity are increasing including multimedia communication to PC peripheral devices including Digital Still Cameras; Camcorders, MP3 players and mobile phones. Applications for mobile networking have a broad scope as they can be applied to many situations in either industrial or commercial sectors. The take-up will depend on the perceived benefits of future applications and whether the differences in quality of service will overcome higher user charges. For example, the quality of service for a voice-over-IP which can

be offered over Wi-Fi connecting to an IP network versus the high quality of a voice service over 3G networks (Laroia et al, 2004 and WiMax-Forum, 2007).

The Mobile Networking Industry Value Chain The approach taken in the business planning framework is to establish the focus and scope of business activities (Afuah and Bahram, 1995), with respect to the positioning of the firm in the industry value chain. The industry value chain for the mobile networking sector is shown in Figure 2. It comprises many high technology companies which have specialist expertise and manufacturing capabilities. The industry value chain for the mobile networking sector comprises three elements from upstream to downstream as follows: vendors, technology providers and the end user network as shown in Table 3. Firms have developed their mobile networking expertise in-house or externally, for example, acquiring specialist technology companies with audio recognition software that improves the audio performance of any voice-based product or system. Many firms use specialists to provide network monitoring equipment aimed at data acquisition for the purposes of remote monitoring including the monitoring

Figure 2. Industry value chain for mobile networking products Embedded devices

IC supplier

ODM

End user network

Major brands

Network Provider

ASICs

Networking Module Supplier Protocol stacks

Software specialists

Auxilliary devices

Standalone Network

Channels Configuration etc..

Networking specialists

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of equipment operation at unmanned sites or as automated disaster prevention systems. The shortening of product lifecycles increases pressures on the management of product innovation activities to reduce time-to-market. Specialising within the industry value chain firms is a means for achieving this for high technology firms operating in highly uncertain markets such as mobile networking where the applications are still emerging (Bria et al, 2001). The scope of activities that a firm provides within the industry value chain is part of the strategic focus of a firm (Afuah and Bahram, 1995). The companies specialize within the industry value chain for mobile networking products which comprises a number of high technology firms each developing technologies and products for deployment in international markets. The advantages of

this approach (of having a devolved value chain), is that firms are utilising reduced transaction costs and economies of scale (WiMax forum, 2004). This is particularly relevant for mobile networking applications where solutions encompass a variety of technological approaches in terms of wireless encoding, data communication and networking protocols. The other benefits of having the value chain being provided by different organisations is that the business is more flexible as, unlike a large corporation, the corporate structure is more easily changed (Floricel and Miller, 2003). The organisation is also more responsive to changes in market conditions as each of the various firms in the network is monitoring the market (Stuart, 2000).

Table 3. Summary of the elements of the mobile networking industry value chain Upstream Elements

IC (Integrated Circuit) Suppliers (including ASICs – application specific ICs)

ASICs and other specialised ICs are a key part of mobile networking products and the companies with the design capability for this may not necessarily manufacture the ICs themselves

Networking Module Suppliers

Firms that provide the hardware components including the circuit board, antennas, transceivers and base process units

Software Specialists

Firms that provide the software necessary to handle the end user application (or interface to an existing application) plus the communications and networking functionality required

Midstream Elements Original Device Manufacturers (ODMs)

Firms who supply electronics equipment that they require to become wireless enabled

Major Brands

The major electronics companies – typically global consumer electronics companies with an established market brand

Channels (to market)

These are the distribution channels providing mobile user devices to consumers (e.g. high street retailers)

Downstream Elements

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Network Providers

These are typically large service providers (including mobile phone operators)

Standalone Networks

Firms providing industrial networks (e.g. in oil refineries)

Networking Specialists

These are typically consultants with expertise in the configuration, installation and operational aspects of communication networks (including technical and other performance issues)

A Business Planning Framework for WiMAX Applications

Innovation Application Market driven management starts with the definition of the target customers and their applications. This concurs with the view taken here since a firm’s focus on specified target customers will define the parameters of the product/ service offering. Consumer products are characterized by large volume and very tight cost pressures on the producer. To achieve a comparative advantage requires technology firms to develop their technology understanding prior to volume market launch. They then utilize their market knowledge to launch desirable product configurations (Orihata and Watanabe, 2000). The chosen innovation applications are often dependent on a firm’s legacy, its core competences, and its reasons for moving into the mobile networking sector and recent product development activities. This focus on specific applications is necessary to establish the functionality provided by the mobile networking products and optimise the mobile networking solution to the end application. WiMAX uptake may benefit from the increasing number of mobile user devices which are available both for industrial purposes (such as handheld terminals) and for consumer electronics. Healthcare is an area where we are likely to see a proliferation of “always-on”, battery-powered devices both in the home and in hospitals. Home networking is an area which has been recognised but has not yet seen great diffusion. This will entail linking devices together and exchanging information so that a high level of automation is achieved, hence, driving the potential demand for WiMAX.

taken in the business planning framework is to evaluate a firm’s competitive performance in the mobile networking sector on the three aspects of: resources; market position and financial performance. These factors were identified by Hunt (1999) in the work developing the RA (resourceadvantage) theory of competition. The reasons for adopting this theoretical framework is that it combines the literature on the resource-based view (RBV) of the firm as well as the literature on strategic positioning or market based view (MBV). As technology advances it becomes increasingly difficult for firms to have sufficient resources of sufficient breadth and depth in the required technological areas. This necessitates the need to create a business model involving collaboration as technology firms are driven by resource limitations. The importance of business models is that they can assist firms in their quest for developing competitive advantage on an ongoing basis. As technology becomes more common, competition may shift away from technology to other areas (Friar and Horwich cited in Lemos and Porto, 1998). WiMAX as a mobile networking application enables equipment providers to have a much closer relationship with the end users of their broadband wireless access service. There is the opportunity for technology firms to gain insights into user aspects which enable them to improve their future product offering in terms of interactive design and other user-centred design aspects. This knowledge can provide a firm with competitive intelligence that should enable the firm to maintain a competitive advantage (Lemos and Porto, 1998).

Competitive Strategies

Key Components of the Business Case

The strategic orientation of a firm in highly uncertain markets requires three areas of focus according to Gatignon and Xuereb (1997): customer; competitors and technological. The approach

A business case assessment should identify the proposal’s potential contribution to the overall performance of the firm (Loch, 2000). Business planning involves understanding the drivers of

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A Business Planning Framework for WiMAX Applications

value both for the firm creating the product/ service and the customer purchasing it (Ryan, 2004, pp. 81). From the firm’s perspective the business case should examine whether the value of the future stream of net cash exceeds the initial cash outlay required for a business proposal (Hawawini and Viallet, 2007, p.5). Business models should not be restricted to pricing and revenue models but should also address the following according to Osterwalder and Pigneur (2002): the value proposition of the proposed product innovation; customer management; infrastructure management and financial aspects. Infrastructure management comprises the following according to Osterwalder and Pigneur (2002): capabilities and resources; value configuration and partnerships. This is reflected in Figure 1 with the “innovation models” allowing for internal resources as well as collaborations.

Innovation Models Innovation models identifies the approach a firm takes to organising itself for undertaking the development work necessary to develop the new products/ services. Essentially it is a “business model” for the firm’s activities relating to innovation which describes the key development activities. Technology core competencies for mobile networking firms are multi-disciplinary. Existing technology firms are unlikely to have developed expertise in all the required areas. To develop mobile networking products and services they need to identify the expertise that should be developed to support the development of the required products (McEvily et al, 2004). It is necessary to establish the costs of the technological innovation and product development activities which firms have undertaken to develop products in the mobile networking sector. The trend is towards product development using business partnerships with other vendors who have hardware expertise and product portfolios that will enable a firm to realise their technology development strategy. This is increasingly 440

necessary as mobile networking firms encounter a wider range of consumer electronic scenarios including streaming CD-quality audio; digital image transfer and laser printing where bandwidth and power are critical factors.

Collaborations Business partnerships are a fundamental change and affect the way in which businesses are organised and managed. Companies are able to retain within the organisation only the activities or processes that best meet their competencies and provide optimum value-add. The reduced resources are focused on a given activity (or set of activities) that are revised and refined till a high degree of sophistication and speed is achieved. The business case framework shown in Figure 1 recognises that it is common practice to utilise business partnerships and collaborations during development work. This is particularly true for end user mobile devices where the shortening of product lifecycles increases pressures for innovation activities to reduce time-to-market. Fast development processes enable firms to exploit the emerging innovation opportunities which arise from the interaction among components once new technologies are in place. These new innovation opportunities were not apparent prior to launch of the new technologies and result from the interactions. This is apparent in mobile networking as more and more user applications are being realised after systems have been deployed in the field. Innovation strategies that involve other firms requires an organisational commitment to the pursuit of a chosen product development with another organisation. Despite this alliances have been recognized as providing efficiency and greater creativity for new product development. Both of these are key to addressing the issue of sustainability of competitive advantage. Faster renewal of resources and products is achieved which is necessary to counter changes of markets, competitors and technological advancements.

A Business Planning Framework for WiMAX Applications

Resources Ryan (2004, p.272) identified that the financial planning for a business case should comprise three parts:

ing to Ryan (2004, p.272); are dependent on the internal constraints of a firm and external opportunities that the business confronts as shown in Table 4.

Innovation Forecasts 1. 2.

3.

The revenue model which describes how the new business activity will win revenue The expenditure model which describes the necessary expenditures required to achieve the goals specified by the revenue model The financing model which describes how the firm will raise its finance

Forecasts are then created based on the projections made for these three parts. The forecasts should consider the value proposition over the entirety of the value life cycle which according to Osterwalder and Pigneur (2002), comprises: value creation; purchase; consumption, renewal or transfer. The scenario for the provision of broadband wireless access is rather different as user costs are predominantly service access charges (e.g. subscriptions); rather than the equipment purchased. The business case is altered so that the revenue is generated over the lifetime usage of the equipment rather than the initial purchase price. This approach focuses on the service provider providing end users connectivity to the Internet via broadband wireless rather focusing on the mobile user devices. The two items of interest here are the revenue model and the expenditure model which, accord-

Forecasting essentially requires an understanding of the broad area beforehand (Cuhls, 2003). This more general establishment of the future context is known as foresight and often starts with the identification of the one or the different options for the future. By nature foresight is more qualitative that quantitative and usually precedes detailed forecasting which is more quantitative in nature. The qualitative approach to financial forecasting has limits (Kesh and Raja, 2005), but can be adopted for specific applications. The approach requires a high level of clarity of terms and establishing a relationship amongst the elements. The relationship could be a hierarchical arrangement which defines the necessary logic behind the elements in a model for financial forecasting (Lemos and Porto, 1998). The experiences of the electronics sector in providing mobile handsets in large volumes to short market windows is unlikely to be the pattern for WiMAX adoption. A switch to mobile networking applications will not only involve potential forecasting difficulties in terms of market research amongst WiMAX end users (McBurney et al, 2002) but also organisational forecasting problems (Sand-

Table 4. Internal and external factors affecting the business case The revenue model: External revenue drivers:

Markets, competition etc..

Internal revenue drivers:

Capabilities and USPs etc..

The expenditure model: External cost drivers:

Supply chain characteristics, labour conditions etc..

Internal cost drivers:

Organisational structures, technologies in place etc..

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ers, 1995) amongst the network operators who are not used to this business approach. Resistance to adopting new financial forecasts is likely to occur until such a time that field trials enable forecasts to be evaluated (Sanders, 1995). The difficulties of forecasting broadband wireless access service provision are due to the lack of established applications and that timescales for the forecasted positive net cash flow are lengthy. One approach to overcoming organisational forecasting problems is to develop co-operative strategies (Sanders, 1995).

Scenarios Financial planning requires quantifying the expected cash flows for the innovation opportunities. As WiMAX mobile networking applications are not yet deployed it is not possible to measure cash inflow from operations. The implication for examining the business case for WiMAX applications is that one of a number of alternative valuation methods will need to be proposed. Scenarios are a method of approaching this by recognising a potential future state which can then be evaluated financially by means of forecasting. Forecasting market demand for new telecommunications services cannot make use of historical market data which makes scenario analysis methods an attractive approach to modelling the dynamics of a marketplace (McBurney et al, 2002). WiMAX is likely to benefit from both increased capacity demand from the industrial sector as well as the consumer sector which has a large number of consumer devices which are Wi-Fi enabled. Industrial applications range from temperature monitoring, security, industrial monitoring and building automation markets through to medical, automotive, retail (particularly electronic point of sale) and factory automation. It is difficult to assess potential user interest in the case of technology that is novel and largely unknown to the market. While the provision of Internet services is well established, the value to customers of telecoms

442

services being delivered by WiMax is unclear at present. The end user will need to be reassured that emergency delivery of calls is guaranteed and that adequate technical support is available.

Costs Quantifying the costs of deploying WiMAX mobile networking applications requires understanding the different costs involved. The categorisation of costs was identified earlier (in Table 1) as: • • • • •

Spectrum Licence fees Planning costs Equipment costs Deployment costs Operating costs – this refers to ongoing network support costs and will not be discussed further here.

Spectrum licence fees are potentially prohibitive costs in terms of the business case. Regulatory constraints are a factor for WiMAX as the availability of radio spectrum is a regulatory constraint. Much of the spectrum needed to deploy WiMAX has already been distributed by governments or dedicated for other purposes by network operators (Vaughan-Nichols, 2004). Planning costs are not the issue in themselves as it usually involves a radio planning group examining the geographic location and determining performance parameters. The issue is more the implications of the findings of the planners as these will impact the amount of equipment required to be deployed. The performance of the radio transmissions are affected by the radio frequency which in turn affects radio planning, for example, in determining cell capacity (Fong et al, 2004). Equipment costs vary depending on how closely tied a service provider is to a vendor. Proprietary wireless solutions incur higher equipment costs as equipment vendors have to recover substantial development costs. In contrast, global

A Business Planning Framework for WiMAX Applications

standards enable development costs to be spread across the wider community of high technology companies. Further, the overall adoption rate is slower than established standards such as Wi-Fi (wireless LAN), particularly in terms of equipment such as access points and end user devices. The methodology for forecasting costs for next-generation wireless applications is based on a mixture of three considerations: 1. 2. 3.

Historic cost Modelling of equipment Equipment cost decline trends

Historic cost forms the basis on which telecoms networks are costed. The experience of deploying and running a network provides the baseline information for service providers on which they formulate future cost assumptions. In contrast; establishing the amount of equipment to be deployed is based on the anticipated capacity requirements. This provisioning of equipment is in turn is based on forecasts for the take-up of broadband wireless access services. The business case for broadband wireless access in areas where there is no established access network (e.g. developing countries or rural areas), is likely to differ to the business case for traditional access networks that incurred high costs of core switching equipment and access network deployment. However, backhaul costs are still expensive (Gunasekaran and Harmantzis, 2005). The future IP (Internet protocol), based core network will use a variety of access technologies to connect users (Becher et al, 2001). The costs of communications equipment for the core network are dropping and the components for end user devices are evolving into becoming multifunctional. The IP products in the core network are likely to be provided by other specialist organisations who would supply them to the service provider. For example, application developers, device manufacturers, system integrators and application service providers.

Deployment economics are a key concern for network operators (Koffman and Roman, 2002) as visiting customer homes to install and configure equipment is a resource intensive business. Recent laptops are now fitted with Wi-Fi access cards and users are able to setup and configure a wireless LAN in their home themselves. This reduces the deployment costs and also speeds up roll-out of broadband wireless access on a large-scale. At present most user devices do not have a WiMAX radio interface card fitted. The future trend is likely that radio interfaces in mobile Internet and consumer electronic devices will support several radio interfaces and possibly have the potential to download upgrades (Becher et al, 2001 and Ohmori et al, 2000).

FUTURE TRENDS Business planning for mobile networking applications needs to consider the perspectives of the equipment providers; the service providers and the end-user. The equipment providers typically incur high development costs and the associated operating expenditure model during production. In contrast, the service providers are concerned with network configuration, deployment economics and operating costs. There are a number of areas where mobile networking applications will offer new opportunities, including e-Home and in-car information and entertainment systems. Social networking is (Alam and Prasad, 2007): “A platform where people from all walks of life come together to express themselves by means of sharing videos, pictures, contents, etc.. and it provides the ability to collaborate using peer-to-peer applications and services”. The trend towards social networking is potentially a global one which could alter the dynamics of capacity utilisation amongst residential users of broadband wireless access. Financial planning requires quantifying the expected cash flows for these market opportuni-

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A Business Planning Framework for WiMAX Applications

ties. The business case for WiMAX applications needs to be flexible enough to evaluate mobile user services for which the sales growth rate is undetermined. As WiMAX mobile networking applications are not yet deployed it is not possible to measure cash inflow from current operations.

when forecasting demand for emerging services for which historical data is not available.

REFERENCES Afuah, A. N., & Bahram, N. (1995). The hypercube of innovation. Research Policy, 24(1), 51-76.

CONCLUSIONS The chapter started with a description of the potential of a WiMAX communication system to provide mobile networking services. This utilises the point-to-multipoint configuration of the WiMAX standard to provide a broadband wireless access solution. In the context of value management with its emphasis on creating and delivering value, a business planning framework has been introduced. This comprises two sides which need to be in alignment. With respect to examining the market potential the market requirements are examined along with competitive positioning. With respect to the business case a discussion of innovation models was made that recognises the various dimensions of innovation management and resourcing. Concerning the forecasting of future demand for emerging broadband wireless applications the approach proposed is scenario based that recognises the globalisation of services and applications such as Face Book. The presented business planning framework for mobile networking technologies provides a means of matching market-induced variability to the organisational issues and systems necessary for technological innovation. The framework draws on principles grounded in financial management, marketing management strategy and innovation management. By utilising an open-systems view of innovation management in the business planning framework it supports generic approaches to planning innovation for emerging broadband wireless applications. Further it recognises the challenges of providing quantitative forecasts

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Alam, M., & Prasad, N. (2008). Convergence transforms digital home: techno-economic impact. Wireless Personal Communications, 44(1), 75-93. Anderson, J. C., & Narus, J. A. (2004). Business market management – understanding, creating and delivering value. Upper Saddle River, NJ: Pearson Education, Inc. Ballon, P. (2007). Changing business models for Europe’s mobile telecommunications industry: The impact of alternative wireless technologies. Telematics and Informatics, 24(3), 192-205. Becher, R., Dillinger, M., Haardt, M., & Mohr, W. (2001). Broadband wireless access and future communication networks. Proceedings of the IEEE, 89(1), 58-75. Bria, A., Gessler, F., Queseth, O., Stridh, R., Unbehaun, M., Wu, J., & Zander, J. (2001). 4th-generation wireless infrastructures: scenarios and research challenges. IEEE Personal Communications, 8(6), 25-31. Cuhls, K. (2003). From forecasting to foresight processes - new participative foresight activities in Germany. Journal of Forecasting, 22(2-3), 93-111. Floricel, S., & Miller, R. (2003). An exploratory comparison of the management of innovation in the New and Old economies. R&D Management, 33(5), 501-525. Fong, B., Ansari, N., Fong, A. C. M., Hong, G. Y., & Rapaji, P. B. (2004). On the scalability of fixed broadband wireless access network deploy-

A Business Planning Framework for WiMAX Applications

ment. IEEE Communications Magazine, 42(9), S12- S18. Galperin, H. (2005). Wireless networks and rural development: opportunities for latin america. MIT Press Journal of Information Technologies and International Development, 2(3), 47-56. Gatignon, H., & Xuereb, J. M. (1997). Strategic orientation of the firm and new product performance. Journal of Marketing Research, 34(1), 77-90. Ghosh, A., Wolter, D. R., Andrews, J. G., & Chen, R. (2005). Broadband wireless access with WiMax/802.16: current performance benchmarks and future potential. IEEE Communications Magazine, 43(2), 129-136. Gunasekaran, V., & Harmantzis, F. C. (2005). Affordable infrastructure for deploying WiMAX systems: mesh v. non mesh. IEEE 61st Vehicular Technology Conference, (5), 2979- 2983. Hawawini, G., & Viallet, C. (2007). Finance for executives – managing for value creation. Mason, Ohio: Thomson South-Western. Hunt, S. D. (1999). A general theory of competition: resources, competences, productivity, economic growth. London: Sage Publications.

Lemos, A. D., & Porto, A. C. (1998). Technological forecasting techniques and competitive intelligence: tools for improving the innovation process. Journal of Industrial Management & Data Systems, 98(7), 330 – 337. Loch, C. (2000). Tailoring product development to strategy: case of a European technology manufacturer. European Management Journal, 18(3), 246-258. McBurney, P., Parsons, S., & Green, J. (2002). Forecasting market demand for new telecommunications services: an introduction. Journal of Telematics and Informatics, 19(3), 225-249. McEvily, S. K., Eisenhardt, K. M., & Prescott, J. E. (2004). The global acquisition, leverage, and protection of technological competencies. Strategic Management Journal, 25. 713–722. Ohmori, S., Yamao, Y., & Nakajima, N. (2000). The future generations of mobile communications based on broadband access technologies. IEEE Communications Magazine, 38(12), 134- 142. Orihata, M., & Watanabe, C. (2000). Evolutional dynamics of product innovation: the case of consumer electronics. Technovation, 20(8), 437-449.

Kesh, S., & Raja, M. K. (2005). Development of a qualitative reasoning model for financial forecasting. Information Management & Computer Security, 13(2), 167-179.

Osterwalder, A., & Pigneur, Y. (2002). Business models and their elements. Paper presented at the International Workshop on Business Models, Lausanne, Switzerland.

Koffman, I. & Roman, V. (2002). Broadband Wireless Access Solutions Based on OFDM Access in IEEE 802.16. IEEE Communications Magazine, 40(4), pp. 96-103.

Petkovic Y., & De Coster, R. (2000). Broadband Access: New Business Models. London: Ovum Ltd.

Laroia, R., Uppala, S., & Li, J. (2004). Designing a mobile broadband wireless access network. IEEE Signal Processing Magazine, 21(5), 20- 28. Lehr, W., & McKnight, L. W. (2003). Wireless internet access: 3G vs. WiFi? Telecommunications Policy, 27(5-6), 351-370.

Ryan, B. (2004). Finance and accounting for business. London: Thomson Learning. Sanders, N. R. (1995). Managing the forecasting function. Journal of Industrial Management & Data Systems, 95(4), 12 – 18. Stuart, T. E. (2000). Interorganizational alliances and the performance of firms: a study of growth

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and innovation rates in a high-technology industry. Strategic Management Journal, 21(8), 791-811. Vaughan-Nichols, S. J. (2004). Achieving wireless broadband with WiMax. IEEE Computer, 37(6), 10- 13. WiMax-Forum. (2004). Regulatory position and goals of the WiMAX forum. Retrieved May 14, 2008, from http://www.wimaxforum. org/news/downloads/WiMAX_Forum_Regulatory_Whitepaper_v06162004.pdf. WiMax-Forum. (2007). IEEE 802.16a Standard and WiMAX Igniting Broadband Wireless Access. Retrieved May 14, 2008, from http://www. wimaxforum.org/news/downloads/WiMAXWhitepaper.pdf. Zhang, M., & Wolff, R. S. (2004). Crossing the digital divide: cost-effective broadband wireless access for rural and remote areas. IEEE Communications Magazine, 42(2), 99- 105.

Key Terms Business Case: Development of a business proposal including the evaluation of resources

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and finances including the assessment of the likely earning potential of new products or applications. Business Planning: The process of identifying likely cash flows and examining the sensitivity of these likely cash flows from which targets are established for managing the business development including resourcing. Forecasting: Preparing predicted customer and market take-up of specific applications which form the basis on which investment criteria are examined. Mobile Networking: Wireless technologies which provide communications between devices, for example, a laptop maybe connected wirelessly to a printer via radio using the Bluetooth standard. Scenario Planning: An approach to forecasting which examines likely market situations (or scenarios) based on qualitative research into users and markets which can then be extrapolated into quantitative forecasts.

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Chapter XXVIII

Adoption of VoIP Applications in Public and Private Organizations Nicoletta Corrocher Bocconi University, Italy and University of Tromso, Norway Roberto Fontana University of Pavia, Italy and Bocconi University, Italy Claudia Parlanti Bocconi University, Italy

Abstract We provide evidence on the determinants of diffusion of Voice over IP (VoIP) applications in a sample of public and private organizations in Italy. We first review the recent developments in the technology in order to identify the current trends and the costs and benefits of VoIP adoption. Second, we discuss the recent policy efforts at the European level toward the implementation of the technology. Third, we present an empirical investigation. Our results suggest that organizations become more likely to adopt as time goes by, and that the decision to adopt is mostly affected by size and availability of financial resources. Organizations can benefit from IP communications systems, because they offer cost savings and enhanced applications facilitating network management and on-line transactions. However, technical shortcomings, established habits and practices, and legacy network investments can inhibit adoption. This explains why firms are more likely to adopt as time passes and why small organizations are more inclined to adopt than larger ones.

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Adoption of VoIP Applications in Public and Private Organizations

INTRODUCTION The growth of the Internet Protocol (IP) has raised the issue of a possible migration from traditional circuit-switched networks designed for basic voice communication towards shared packet transport handling a mix of applications. A substantial number of different services and solutions are currently available for businesses, such as advanced IP telephony calling and management, Web, audio and videoconferencing, instant messaging, calendar and other PIM functions, email, fax, and voicemail. IP Communication lowers costs of network management, since it eliminates the need for different infrastructures. It simplifies maintenance and allows quickly reactions to the changing needs of businesses. However, cost reductions are just one part of the story. Indeed, IP-based networks enhance business communications by providing a flexible foundation upon which all types of new applications and services can be deployed, quickly and easily. Solutions like IP telephony, unified messaging, and IP contact centre have been designed to support increasingly mobile workforce. For instance, unified messaging solutions deliver any message into a single inbox, allowing employees to access and manage their communications with any device. These applications improve communications by facilitating increased mobility, delivering advanced functionality, and streamlining administrative tasks. As a result, employees are able to communicate more effectively and can focus on activities that create new revenue streams or generate cost savings. However, although the technology has been constantly improved, there remain some technical problems for the provision of IP Communications, which are related to the characteristics of the IP network, such as voice quality and network reliability, legacy investments, and regulation. This chapter has three aims. First it will provide a review of the recent developments in the technology in order to identify the current trends and their impact on the costs and benefits of Voice

448

over IP (VoIP) adoption. Second, it will briefly discuss the recent policy efforts, especially at the European Union level, toward the implementation of the general framework approved in 2003. Third, on the basis of these premises, it will present an empirical investigation of the determinants of the adoption of VoIP Communication by public (i.e. Universities, Hospital, Public Administration offices) and private organisations (i.e. Banks and other types of enterprises), in order to identify drivers and obstacles of the diffusion of this technology. In particular, we intend to understand what firm-specific and market-specific variables drive individual adoption. The empirical contribution of the chapter relies upon an original dataset including 123 Italian organisations that have adopted VoIP Communication solutions since from 2001 (when VoIP Communication was first introduced in Italy) until 2007.

Background: The characteristics of VoIP technology Voice over IP services refer to the transmission of voice and data over the IP network. This application may be also implemented over any form of the IP network, including Local Area Networks and corporate Intranets. VoIP converts the voice from analogue signals to a series of digits, bundles the data into packets and transmits these packets over the network. Early Internet phones evolved either as by-products from the videoconference industry or from companies like VocalTec, the first firm to use Internet telephony in a computer application in 1995. This service was initially available only to users with a computer connected to the Internet. However, following the continuous technological evolution, the cost saving benefits of Internet telephony have become available to any user with a telephone connected to the public switched telephone network (PSTN) (Babbage et al., 1997; Ono and Aoki, 1998).

Adoption of VoIP Applications in Public and Private Organizations

There are three classes of Internet telephony: PC-to-PC; phone-to-PC (or PC-to-phone); phoneto-phone (Clark, 1997). In the PC-to-PC configuration, both computers are linked directly to the Internet and voice packets travel entirely over a packet-switched network. The phone-to-PC and PC-to-phone models of Internet telephony require the installation of a gateway which links the Internet to the PSTN and sets up a connection with a remote gateway at the other end of the call, in order to ensure compatibility between the two networks. Outgoing calls from a PC to a phone are simpler than calls travelling in the opposite direction, since it is relatively easy for an Internet phone application to find a phone number and the IP address of the gateway, while it is impractical to require the PSTN users to dial first the telephone number of a gateway and then the numeric IP address of the called party (Babbage et al., 1997; Kuprinski, 1997). Phone-to-PC users receive regular phone calls during an Internet session. A window notifies an on-line user of an incoming call and they take the call over the PC while remaining connected to the Internet. The third configuration of Internet telephony is phone-tophone. In this type of model, the caller’s phone is connected to a gateway which transforms voice into IP packets and sends them over the Internet to another gateway. This gateway converts the digital signals into analogue signals and routes the call through the local PSTN, which in turn transmits the call to the telephone of the called party. VoIP services are also being used by corporate users as an alternative means to enable voice communications (OECD, 2006). There are mainly three types of corporate VoIP services: gateway type, which adds gateways to a traditional private branch exchange (a telephony system to switch calls between corporate users on local lines while allowing all users to share a certain number of external telephone lines); IP-PBX type, which permits all controls for switching calls implemented by PBX to be managed over the IP; IP Centrex type, which implements outsourcing installation,

operation and management of IP networks to telecommunications operators. This notion is very broad and includes both consumer and business application. The former implies point-to-point and point-multipoint communications; the latter only multipoint-to-multipoint ones. The development of broadband and wireless connections has led to a wide diffusion of the Internet and, consequently, of IP-related applications also for businesses. In this context, many consider IP Communication as a killer application for the diffusion of broadband connections (OECD, 2006). “IP Communication refers to the integration of data, voice and video solution into a single Internet Protocol (IP) - based network”. As a consequence, a large amount of different services and solutions are available for business application: advanced IP telephony calls and management, Web, audio-, video calls and videoconferencing, instant messaging, file sharing, calendar and other similar functions, email, fax, and voicemail, personal virtual assistance. An IP Communication-based network favours not only the exploitation, but also the convergence of different applications and in this way it allows an increase in services’ quality and efficiency increase and, more than that, a decrease in network management costs.

The Advantages of IP Communication IP Communication solutions have been available for some years. However, their diffusion among businesses and public organisations is still in its infancy, especially in countries that are late comers with reference to ICT adoption such as Italy. One of the most important reasons for this delay lies in the perception of the benefits deriving from IP communication. The conventional perception on convergence considers cost savings as the most compelling initial benefit of VoIP. A more progressive revenue path can be determined if companies start thinking about these applications

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Adoption of VoIP Applications in Public and Private Organizations

according to their profitability, to the increase in efficiency or capability the new service introduces, to the maturity of the technology. In this respect, a common strategy based upon an infrastructure viewpoint is to first implement phone-to-phone services, then some value-added services. The resulting path starts from the development of mission critical services that add no value for the user and rely upon immature or developing platforms. A more suitable strategy would be to provide first a service that has value-added for the user, is not yet mission critical and is based on an emerging platform. As the technology matures, providers increasingly run existing services on the new platform (Corrocher, 2002). In terms of cost reduction, IP Communication lowers the total cost of network management, by eliminating multiple sets of infrastructure, simplifying system administration and maintenance and consolidating voice and data circuits. Moreover, a single network permits to scale for the future and quickly react to the dynamically changing needs of the business. With reference to reduction in equipment and maintenance costs, we can observe that a converged network combines multiple network infrastructure into a single IPbased network, allows firms to centralize call processing, reduces the number of wiring drops in a new facility by 33% to 50% per user and lowers hardware connection costs, by reducing or even eliminating PBX/ACD upgrade costs. IP Communication also enables organisations to reduce network administration costs, by improving the productivity of network support staff through simplified network management, by minimizing outsourcing costs and by enabling network support staff to manage much larger user communities. Third, a converged network allows reducing network carrier costs. If we turn to examine application-centric benefits, IP-based network enhances business communications, by providing a flexible infrastructure upon which all new applications and services can be easily deployed. These applica-

450

tions improve communications by facilitating increased mobility, delivering advanced functionality, and streamlining administrative tasks. As a result, employees are able to communicate more effectively and can focus on activities that create new revenue streams. With reference to this, IP Communication solutions are particularly beneficial for companies whose employees are often out of the office, since they remove geographical barriers and allow them to work from anywhere. Solutions like IP telephony, unified messaging, and IP contact centres have been designed to support today increasingly mobile workforce. For instance, unified messaging solutions deliver any type of message into a single inbox, giving employees the ability to access and manage their communications with different devices. Moreover, personal communication assistants help employees to be reachable anytime anywhere.

Problems and Open Issues in the Transition to IP Communication Although the technology has been constantly improved, there remain some technical and regulatory problems for the provision of VoIP, which are mostly related to the characteristics of the IP network. These problems concern, on the one hand, quality of service (QoS), service reliability, and network migration; on the other hand they are related to the categorization of IP services within the general framework of communications services. QoS might be undermined because packetswitched networks do not dedicate a path between the sender and the receiver. This means that each packet of information (voice, data or video) shares the available bandwidth with other packets. The packets sent through the Internet arrive at destination by a variety of sources and in any chronological order: they are accepted on a best-effort basis and can be delayed or lost. This implies that quality of service cannot be guaranteed. The more packets are lost, the more interpolation is needed

Adoption of VoIP Applications in Public and Private Organizations

and the more likely that the receiver of the call will hear distortion. Latency - the delay between when one party sends the voice/data message and the other hears/receives it - represents another important technical shortcoming (Howard et al., 1998). Other factors such as network ability to recover the original signals, quality of computing resources, voice processor and technical methods to establish connection between users are likely to affect the performance of IP communication solutions. Reliability is also a critical concern for companies that are engaging in a network convergence process. By implementing the correct design, converged networks running VoIP can achieve a comparable level of reliability to the traditional network. The additional benefit of building redundancy into a converged network is that organizations can also improve the reliability of their data and video traffic. As far as the problem of migration to new networking solutions is concerned, the issue relates to companies’ willing to protect existing investments, while migrating separate networks to a converged networking model. These investments include contractual agreements with service providers, which are generally long-term for local-government, education and healthcare organisations. In relation to this, most converged networking vendors have been developing products to ease this transition and ensure that new equipment can integrate with the existing infrastructure. Finally, there is a lack of a clear international regulation about IP-based communications services. In 2003, the European Commission approved a general framework, which determines stronger restrictions for telecommunication incumbents than for independent providers. Currently, the main issues under investigation by regulatory authorities concern localization of users and emergency services, geographical numbers’ provision, extra-territory service providers’ presence, a standard quality of service and network reliability.

The main focus: A framework for the analysis of the adoption of IP communications When studying individual choices of technology adoption, the empirical literature generally focuses on three sets of determinants: attributes of the technology, adopters’ characteristics, and features of the competitive environment. Among adopters’ characteristics, firm size, R&D expenditures, age, and capabilities are usually considered among the main determinants. The competitive environment can be described by the degree of firm concentration, the level of prices, and the existence of informational spillovers among potential users. Attributes of the innovation are usually related to technical features (i.e. compatibility with existing solutions) and may vary depending on the perception of potential adopters. If we consider adoption of new technologies by public and private organisation, the decision to adopt is motivated by a series of factors such as the need of increasing operational efficiency, the willingness to improve market reach and profitability, and the need to manage risks (Daniel and Grimshaw, 2002). Several attributes of innovations act as drivers or obstacles of adoption. First and foremost, innovations must possess a relative advantage over the existing ideas. According to Rogers (1995), when a new technology emerges, individuals evaluate both its economic profitability and other variables - degree of risk, decrease in discomfort, savings in time and effort, immediacy of rewards. This concept is very similar to the idea of perceived usefulness of the technology, which identifies the subjective probability that using a specific technology would increase one individual job performance (Davis, 1989). Second, the extent to which an innovation is perceived as relatively difficult to understand and use - its complexity or perceived difficulty of use - can hinder the process of technology adoption. Complexity acts as an obstacle to the process of

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technology adoption, since implementing a new technology might require learning both at the individual and at the organisational level. The simplicity of a technology can be related to the capacity of different users to understand and use the technique without a great effort (Davis, 1989; Attewell, 1992; Mole et al., 2004). This idea recalls the notion of absorptive capacity as put forward by Cohen and Levinthal (1990), which identifies the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends. The absorptive capacity is a function of the firm prior related knowledge and characteristics of learning environment. Its development is highly path-dependent, since lack of investment in an area of expertise early on may hinder the future development of a technical capability in that area. Potential users pay great attention also to the compatibility of an innovation, both in terms of technical features and in terms of past experiences and needs. Compatibility is especially important in the case of ICT, whose adoption is affected by the existence of network effects (Farrell and Saloner, 1985; Katz and Shapiro, 1985). In the presence of network effects, the utility from adoption increases in the number of other adopters that purchase the innovation. The trialability of innovations affects adoption since functioning, real world examples are often more important than arguments about advantages and expected functions. Experimenting with a new technology is an important benefit especially for early adopters, since they can only rely upon available information, while laggards can learn from other users’ experience. Finally, an innovation is evaluated according to its observability, i.e. the extent to which its performance and related benefits are perceivable to the users and not only to the companies that produce it. Observability includes both “visibility” - the degree to which the innovation is visible - and “result demonstrability” – the degree to which the results of adopting the innovation are observable and can be communicated to others (Oh et al., 2003). 452

Turning to adopters’ characteristics, one of the most relevant factors taken into account by the empirical literature is firms’ size. This could be measured in many different ways (annual sales, total assets, total revenues and number of employees) depending both on the sector under investigation and on data availability. The role of size in the adoption of innovations is quite controversial, since the existing empirical investigations have produced mixed results. Many authors have found a positive relationship between size and timing of innovation adoption (Hannah and McDowell, 1984; Buzzacchi et al., 1995; Geroski, 2000; Hall-Khan, 2003). At the same time, studying 635 technological changes in the U.S. between 1970 and 1978, Acs and Audretsch (1988) found that small firms produce 2.5 times as many technological changes per employee as did larger firms. Furthermore, some authors (Pennings and Harianto, 1992; Buzzacchi et al., 1995) stress that the growing importance of external sources of technology could reduce the role of size as a determinant of adoption of new technologies. On the one hand, large firms can act as “first movers” in the process of ICT adoption because of the availability of professional competences and lower financial constraints; on the other hand, small firms can be less subject to legacy investments’ constraints and adopt earlier. Other studies (Mohnen and Rosa, 1999; Daniel and Grimshaw, 2002) have underlined that firms’ size might affect the perception of specific benefits and obstacles to innovation, with large firms more concerned about feasibility risks, high costs and uncertainty, and small firms hindered in the adoption by funding difficulties and lack of special equipment. Geographical location can also be an explanatory factor of new technologies’ adoption. The literature has emphasised that firms localized in the same area as other innovative organisations can more easily exploit knowledge spillovers (Acs et al., 1994). As far as ICT services and applications are concerned, several studies have highlighted

Adoption of VoIP Applications in Public and Private Organizations

the importance of location for the adoption/use of innovations (Prieger, 2003; Kim et al, 2006; Arbore and Ordanini, 2006). Firms’ performance, which is usually measured in terms of turnover, profits or value added, has also been investigated as a potential determinant of the adoption of new technologies. Although one could expect a positive relationship between profits and adoption of innovations, the literature does not usually find a significant relationship between the profitability of a firm and the adoption of new technologies. This is true for example for the banking sector, where the absence of such relation is interpreted as the lack of liquidity constraints on the technological strategies of banks (Hannan and McDowell, 1984). Finally, the level of IT literacy and the previous experience in managing advanced technologies constitute important drivers for the propensity to adopt new technologies. These factors reflect the organisations’ technological endowment in terms of inter-firm networking and the IT skills of firms’ human resources. In order to take these variables into account, the literature has adopted different measures such as the presence of LAN, the access to broadband connections, the proportion of IT-skilled employees and the use of ICT services (Pennings and Harianto, 1992; Arduini et al., 2007, Corrocher and Fontana, 2007).

Data Collection and Explanatory Variables

interviews with managers and system engineers of Cisco Systems Italy, which is the worldwide market leader for networking solutions. This was crucial both to choose the possible organizations to be included in the analysis. Second, many complementary electronic resources were used to gain general information, balance sheets and income statements: AIDA, Bankscope and Isis1 for private companies and financial institutions respectively; CINECA (a non profit Inter-University Consortium) and CNVSU (a National Committee for the Evaluation of the academic system) for universities and research centres; and the website of the Health Ministry and of single local government organisations (regions, provinces, and municipalities). Figure 1 reports the composition of our sample. Almost 36% of the sample is made by firms: among these, 45% belong to manufacturing sectors, 32% to non financial services (e.g. consultancy, logistics), and 23% to the financial service sector. Concerning location, Table 1 below reports the joint frequencies of localization by type of activity. The majority of companies (61.2%) are located in the North–West of Italy, especially around Milan, 2.3% in North–East, 27.3% in the Centre and 9.1% in the South. 23.6% of the sample is represented by education organisations and public administrations. Among universities and research centres, 41% is located in the South and 31% List of Figures Figure 1: Composition of the sample

To supplement the review of the technology carried out in the previous sections, we present now a study on the adoption of VoIP in Italy. The study is based on a dataset composed by 123 Italian organisations that have adopted IP Communication solutions from 2001, the year of introduction of IP Communication in Italy, to 2007. These organisations include hospitals and ASL (local healthcare organisations), universities and research centres, local government administrations and firms. Information was first collected through a series of

Figure 1. Composition of the sample

Education, 23.6%

Public Administr., 23.6%

Healthcare, 17.1%

Enterprises, 35.8%

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Adoption of VoIP Applications in Public and Private Organizations

Table 1. Joint frequencies of type of organization by localisation North-West

North-East

Centre

South

Total

Healthcare

10.6%

4.1%

2.4%

0.0%

17.1%

Enterprises

22.0%

9.8%

0.8%

3.3%

35.8%

Public Administration

8.1%

3.3%

4.9%

7.3%

23.6%

Education

7.3%

4.1%

2.4%

9.8%

23.6%

Total

48.0%

21.2%

10.6%

20.3%

100%

in the North–West, while only few of them are located in the Centre (17%) or in the North–East (11%). These organisations on average adopted quite early. Public administrations include five regions, ten provinces, seven municipalities, and seven public companies. They are mostly concentrated in the North–West (34%) and in the South (31%) and generally adopted later than education organisations. Finally, healthcare organisations represent 17.1% of the sample, half of which are hospitals. There are no organizations in the South, and a few in the North-East (14.2%), while the Centre accounts for 23.8% and the North–West has 61% of the sample. Hospitals and ASL can be considered laggards since nobody has adopted before the end of 2005; however, they tend to acquire many IP telephones, especially because of their large size. Intensity of adoption is reported in Figure 2. The lowest level of adoption is represented by just 1 IP phone while the maximum by 9250 phones.

However, only four adopters have more than 4500 IP telephones. Not considering these outliers, the average intensity of adoption is represented by 387 IP phones. Looking at the distribution of this variable illustrated in the graph below, it is easy to see that there is a higher concentration of the sample around lower levels of intensity of adoption. Indeed, almost 40% of the organizations have adopted less than 100 IP phones and actually nearly 23% less than 50. Moreover, the concentration of the sample decreases as the intensity of adoption and the number of IPT acquired increases. Only 37.4% of the organisations have acquired more than 300 IP phones and 20.3% more than 700. This last group is mainly composed by the Public Sector, especially Hospitals and Universities, while enterprises are represented by Banks and Insurances. Finally, we may look at the distribution of the sample in terms of size by intensity of adoption (Table 2).

2: Distribution of intensity of adoption Figure 2. DistributionFigure of intensity of adoption

NumberofIPT 25.0% 20.0%

22.8%

22.8% 20.3% 17.1%

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Adoption of VoIP Applications in Public and Private Organizations

Table 2. Joint frequencies of size by intensity of adoption Size < 300

300 ≤ IPT < 1000

1000 ≤ IPT < 2500

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Size ≥ 4000

Total

IPT < 50

10.6%

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7.3%

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1.6%

2.4%

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4.1%

8.9%

4.9%

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0.8%

4.1%

8.9%

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0.0%

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5.7%

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20.3%

Total

22.8%

24.4%

22.0%

16.3%

14.6%

100.0%

Frequencies in the Table highlight the presence of a positive relationship between these two variables. The larger an organisation is, the higher its level of adoption. Higher frequencies are found at the two opposite sides of the table. On the one hand, 10.6% of organisations with less than 300 employees have adopted less than 50 IP phones. On the other hand, 8.9% of organisations with more than 4000 employees have adopted more than 700 IP phones. In general, organisations in our sample tend to concentrate there in the upper-left and lower-right corners of the Table. At the same time, there are lowest frequencies for large institutions with minor intensity of adoption (0%, 1.6% and 3.3%) and by small organizations with major level of adoption (0%, 1.6% and 0.8%). Higher frequencies are located close to the diagonal. Thus, even medium sized organisations display an intermediate level of adoption intensity.

The Model and the Explanatory Variables To investigate the determinants of VoIP adoption, we carry out a duration analysis. Our dependent variable is binary and takes the value 1 if adoption has occurred in a specific time period and 0 if not. An organisation becomes at risk of adopting after the VoIP has become available in Italy (i.e. January 2001). Time is measured in months since VoIP introduction. We estimate a logistic model with piece-wise constant hazard function. This specification allows splitting the adoption times

at particular points (in our case quarters) so to ensure that events (i.e. adoptions) occur within each of the time intervals. As far as covariates are concerned, we have constructed the following variables. First, we take into account the impact of Size, which is measured in terms of number of employees (in 000s). We expect size to be an important determinant of the diffusion of IP Communication. Many authors have found a positive relationship between size and innovation (Hannah and McDowell, 1984; Buzzacchi et al., 1995; Geroski, 2000; Hall-Khan, 2003). They demonstrate that large firms can act as “first movers” in the process of ICT adoption, since they can increase their image and exploit some advantages, such as relevant financial resources, best human capital and economies of scale and scope. However, other studies have shown that the relationship between size and adoption is much more complex with small and more dynamics firms being faster to adopt and the presence of curvilinear effects and ‘threshold effects’. To account for these possibilities, we also introduce Size2 which is the square of the number of employees. Second, we consider the role of investments. In order to measure these variables, we first homogenise private and public sector balance sheets and then create comparable indicators. Companies with negative CAPEX (expenditures on assets’ acquisition/upgrade) are not considered, since they do not invest in new assets, but rather disinvest their assets. Investments are defined

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Adoption of VoIP Applications in Public and Private Organizations

as the total investments carried out in 2001 (Tot Invest. 01) the year VoIP became available. Since a unique measure of investments in innovation and particularly in ICT is not available, total investments (in 00000s) are used as a proxy. For private companies, we use CAPEX. For hospitals and ASL, we consider tangible assets and maintenance costs. For universities, we use expenditures in human resources and investment goods. Finally, for local government organisations, we use fixed investments. The level of investment is expected to positively influence the adoption of IP Communication. Finally we consider the type of activity of the organisations. Our sample includes four macro categories: healthcare, public administrations, education and private companies. Healthcare includes both private and public hospitals and ASL; Education represents Universities and Research Centres; Public Administrations comprise Municipalities, Districts, and Regions, as well as few firms owned by local government organisations. The variable Public is a dummy equal to 1 if the organisation is public and 0 if not. We expect the type of activity to be an important determinant of adoption of IP Communication. In particular, there are important differences in managerial practices and behaviour between private and public sector. Private companies tend to be more inclined to adopt new technologies, as their structure allows them to take decisions more quickly and easily. Conversely, public organisations should be more reluctant and slow in the process of adoption, especially because of tenders’ mechanisms that slow down the decision process.

Results Table 3 reports our results. Covariates are introduced in sequence. Specification (1) reports the baseline hazard and provides information on how the probability to adopt for the firms in our sample changes as time passes. The estimated coefficients on the duration

456

time intervals are informative about the shape of the baseline hazard function. In particular, we can note that the hazard rises overtime. This result suggests that organisations become more likely to adopt as time passes and is robust to the inclusion of the other covariates in subsequent specifications. In Column (2) we introduce our proxies for size. The coefficient of Size is negative and significant indicating that smaller firms have a relatively higher probability to adopt VoIP than large firms. This result is surprising since previous literature has found a positive relationship between size and the probability to adopt innovations given that large firms generally have more resources available. Our results seem to suggest instead that small firms are more dynamic and adopt earlier then bigger ones. Size2 enters positively and significantly, albeit weakly, indicating that the relationship between size and the probability to adopt is indeed curvilinear. In particular, the probability to adopt decreases as the size of the firm increases up to a certain threshold after which it starts increasing. This result suggests that only very small firms and very big firms have a relative higher probability to adopt. Medium sized firms are those with the lowest probability to adopt. In model (3) we introduce the variable total investment which captures the amount of resources spent by each organisation. This information is not available for all the organisations in our sample. Thus the number of observations in our sample drops from 972 to 499. The coefficient for this variable is positive and significant suggesting, as expected, that the probability to adopt is higher for those organisations that invest more. Interestingly, once we introduce our proxy for the amount of investment carried out by each organisation, our proxy for size loses significance. Indeed, there is a positive correlation between the size of the organisation and the amount of resources available for investment. It is also interesting to note that Size2 remains weakly significant but it becomes negative thus indicating that when controlling

Adoption of VoIP Applications in Public and Private Organizations

Table 3. Determinants of the probability to adopt VoIP for a sample of Italian Organizations tC

( x − C ) dFR ( x);

r

σ ( R) (φ(m) − m Φ(m) ); p Loss = Loss = µ ( R) µ ( R) 2 φ(m) = e ( − m / 2) / 2π ;

90

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t 70 0

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TIME Autocorrelation: Dependencies over time

∞

Φ (m) = ∫ φ( x) d x; m = m

C − µ ( R) . σ ( R)

Dimensioning of link capacities - end of first paragraph, page 855, line 14 The loss rate is computed by:

r Loss

³

( x  C ) dFR ( x);

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of variation σ(R)/µ(R). It can be concluded that C = µ(R) + 3σ(R) is sufficient as a dimensioning rule to obtain loss probabilities below 10 -4, provided that σ(R) / µ(R) < 0.25. Figure 4 suggests that sufficient capacity C for As an example, we evaluate the model for aggregated traffic can be Chapter provided by the rule LIV traffic flows generated by ADSL subscriber lines C = µ(R) + mσ(R) accounting for the mean rate Network planning and dimensioning for broadbandwith access to the Inmaximum rate RMax = 3 Mbit/s, assuming a µ(R) and, in addition, a multiple m of the standard ternet regarding quality of service demands mean utilization pOn = 20% of the access speed deviation. Assuming a Gaussian distribution, the during online sessions. Then we obtain for a single multiple m is determined via the formulas on the Improvedright representation of some tables formulas: traffic source: of Figure 4 depending on figures, a predefined de- andon-off mand for the packet loss rate. The analysis does µ(R) = 600 kbit/s and not include buffering and thus represents a worst Figure 4: Descriptors of traffic variability σ ( R) ≤ µ ( R) (1 − pOn ) / pOn = 2 µ ( R) . case scenario where overload leads to loss of a corresponding fraction of the traffic [8][10]. The Stationary Distribution of the Traffic Rate RT loss rate is computed by: T The on-off source model, which alternates The computation of r Loss takes periods R  into C P(R) + mV(R) A between account, where the traffic rate x exceeds the P(R) + V(R) full access speed and transmission F  F pauses, represents a worst case scenario with the provided capacity C, such that a fraction x – C P(R) I C maximum variance σ2(R) among all distributions cannot be forwarded and is lost without buffers. R A formula refers to a continuous time or fluid of the access rate with the same mean µ(R) and This T t E rate limitation RMax. Then a multiplexed sum S of flow model, whereas the forwarding is done per TIME M homogeneous ADSL traffic flows with those packet.RNevertheless the approach is appropriate, Autocorrelation: Dependencies over time T RT+t parameters has mean rate µ(S) = Mµ(R) and for because the size of IP packets is usually smaller independent flows the standard deviation is than 1500 byte such that thousands of packets are forwarded per second by switches on high Dimensioning link capacities σ (S ) = M σ ( R) ≤ 2 M µ ( R) ⇒ speedoflinks. The calculation starts with regard - end of first paragraph, page 855, line 14 σ (S ) σ ( R) to an arbitrary rate distribution FR (x), whereas = ≤ 2 . µ (S ) The loss rate isthe computed M µ ( R) M packetby:loss probability pLoss is given for a φ(x) with mean µ(R) ( x); r Loss Gaussian C ) dFRdistribution ³ C ( x  rate The latter property implies, that the standard andx !standard deviation σ(R). r V ( R) Loss deviation σ(S) is decreasing with the square root Table 3 shows of m, which are I (m) typical ; p Loss m )(m) values P ( R) P ( R ) of the number M of indepen­dent flows. This sufficient to guarantee loss probabilities pLoss in 2 m / 2) characterizes the smoothing effect of statistical I (m) the e (range /102-3S-; 10 -6 depending on the coefficient f C  P ( R) multiplexing. )(m) ³ I ( x) d x; m . m V ( R) For a link capacity C, the utilization is ρ = Μ µ(R) / C and we obtain a multiple Table 3. Dimensioning for Gaussian traffic: m ≥ (C − Mµ ( R)) /(2 M µ ( R)) . In the examples of 3: Dimensioning for Gaussian traffic: Evaluation of theTable parameter m and thus the rePR)5, mV R) probabilities have been evaluated as Evaluation of the parameter m and thus the required capacityC=Figure loss quired capacity C = m(R) + ms(R) a function of the utilization ρ for a set of usual link for loss probability demand m: C = PR)  m VR) speeds. Aggregation levels in the access from the 10-3 10 -4 10 -5 10 -6 VR)PR) = DSLAM (Digital subscriber line access module) 0.5 2.50 3.17 3.76 4.30 to the backbone network are connected via STM 0.2 2.20 2.92 3.54 4.08 (synchronous transmission module) links starting 0.1 1.94 2.71 3.36 3.92 0.05 1.66 2.50 3.17 3.76 from 155Mbit/s (STM-1), 622Mbit/s (STM-4),

Dimensioning of link capacities

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Network Planning and Dimensioning for Broadband Access to the Internet

Figure 5. Statistical Multiplexing: Loss probabilities obtained for different link speed and load

threshold of allowable link load

100%

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10 G b it/s 2.5 G bit/s

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62 2 M bit/s 15 5 M bit/s

50% 10 -6

1 0- 5

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Demanded loss probability

2.5Gbit/s (STM-16), etc. Assuming that all traffic is generated by ADSL sources with mean rate µ(R) = 600 kbit/s, the multiplexing degree includes slightly more than 250 flows on STM-1 links and more than 1000 on STM-4 links, respectively. It is apparent from those results •

•

That favourable QoS conditions can be met on backbone links even up to utilization levels of 70% – 90%, but are severely affected as soon as this threshold is exceeded. Therefore appropriate safety margins should be subtracted from the threshold in dimensioning rules, That most of the statistical multiplexing gain obviously can be exploited according to the previous analysis without involving buffers.

Nevertheless, the traffic variability in the considered time scale of microbursts is only one of several factors to be included in dimensioning thresholds, where the daily traffic profile as shown in Figure 2 and long term traffic growth processes have to be incorporated leading to further deduction from the allowable utilization level.

In fact, traffic is less homogeneous than assumed in the previous modeling examples. Several source types for ADSL access at different speed as well as traffic entering the network from other platforms, e.g. Ethernet from 10Mb/s to Gb/s speeds have to be taken into account. Inhomogeneous source characteristics detract from the smoothing effect at a considered multiplexing level. On the other hand, there are source types with essentially smoother traffic profile than on-off traffic. Peer-to-peer file sharing applications are expected to down- and upload data in long-lasting transfers without exploiting the full downstream rate. For many source traffic types, the mean and standard deviation is at least approximately known. Comparing video data files, large differences are encountered in the obtainable compression ratio, which make a common classification and control of real time video transmissions difficult. Nevertheless, it is experienced that an aggregation of about 10 or more independent video streams again leads to an approximately Gaussian shape of the traffic rate distribution. The independence of traffic flows as a basic precondition of statistical multiplexing is only

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Network Planning and Dimensioning for Broadband Access to the Internet

valid, if synchronization of sources can be avoided, which might arise from TCP flow control in overload situations. Even if the dimensioning of links and forwarding capacities in telecommunication networks can be efficiently done using the considered zero buffer approach, buffers are necessary not only in the end systems on the sender and receiver side but also in switching elements. Multiplexing of a number of asynchronous links requires some small amount of synchronization buffer and a network-wide support of the TCP window mechanism requires buffer for a complete TCP window size for each flow on its transmission path.

MPLS allows to balance the load among the links of the network. Where shortest routes lead to overload, some demands are shifted to alternative paths in order to balance the traffic flows to make full use of the available capacities. Offline optimization algorithms based on linear programming or simulated annealing are integrated into tools to calculate the most efficient path design [11]. Since quality of service (QoS) properties mainly depend on the load conditions on traversed links, QoS degradations are reduced by adjusted loads or, as a next step, the admissible traffic throughput can be increased while still ensuring a predefined QoS level. It is important to update the path design at least after a topology change or link upgrade. Without employing network wide traffic engineering, Network wide traffic upgrades are triggered separately for each link engineering and load when a load threshold is approached. This was balancing the usual procedure in pure IP networks for a long time in the past. Meanwhile, IP level traffic The deployment of multiprotocol label swit­ching engineering is also proposed by manipulating (MPLS) [14] on ISP platforms opened new opporrouting weights of links, which has some limitatunities for network management and planning. tions. Link weights is a less granular and have a While routing in pure IP networks always follows more complex impact compared to directing each the shortest paths First path, separateexplicit equation data on page 855: (LSPs: label switched paths) can be set up for traffic P(R)flows = 600in kbit/s andflow on a dedicated path. upgrade increases the capacMPLS networks providing the required V ( Rflexibil) d P ( R) (1  pOn ) / pWhen 2Pa( Rlink ). On ity by some factor, then the load on the link is ity to enable designs forontraffic engineering Secondpath separate equation page 855: reduced by the same factor if traffic remains purposes. In addition, standard measurement of ( S ) M ( R ) d 2 M P ( R) Ÿ after the upgrade without redirection V V unchanged path statistics makes the traffic demand matrix V (S ) V ( R) 2 .transmission paths. Even if Figure 1 shows d of available as a basis for network planning. P (S ) M P ( R)

M

Figure 6: Gaps in the link load in in upgrade circles away from redfrom links to minimize overload Figure 6. Gaps in the link load upgrade circles away red links to minimize overload Link utilization 0,5 0,4 0,3 0,2 Utilization on a link with upgrades by factor 4 Utilization on a link with upgrades by factor 2 Threshold for upgrades: 0.5

0,1 0,0 10

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Time [weeks]

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Network Planning and Dimensioning for Broadband Access to the Internet

that fast and steadily increasing Internet traffic will soon fill new transmission capacities, there are large gaps in the utilization curves after link upgrades depending on the increase factor, which is usually 2 or 4 in the STM hierarchy (STM-1 ≅ 155Mb/s; STM-4 ≅ 622Mb/s; STM-16 ≅ 2.5Gb/s; STM-64 ≅ 10Gb/s; etc.) or may be as high as 10 for Ethernet upgrades. Figure 6 illustrates that those gaps can essentially reduce the achievable link load below a desired threshold level during the complete upgrading cycle assuming a steady exponential increases of the traffic. For upgrades to twice the capacity each time when the threshold is reached, the resulting saw tooth curve reaches only 72% of the threshold in the mean and for upgrades to 4-fold capacity only 54%. This effect essentially contributes to low utilization on Internet platforms. A traffic engineering solution reoptimizes the path design on the platform after upgrades and can immediately exploit the newly available capacity by shifting traffic path with regard to network wide load balancing. In addition to the gain by adjusting the load level close to a preset threshold, the flexibility of redirecting paths is valuable especially in failure cases. With regard to failures, a set of relevant scenarios including single link breakdowns can be pre-calculated considering the topology without the affected links [11]. If some of the failure scenarios lead to unavoidable overload on the remaining links, this indicates that the topology isn’t resistant to failures and has to be enhanced with backup capacity. With pre-computed optimum path designs for failure situations at hand, a fast as possible rerouting for the set of modified paths still imposes a challenge. Load balancing has to be applied with care, since it may detract from QoS properties in two ways: •

When paths deviate from the shortest possible route and traverse additional hops this has an impact on the delay and reliability.

•

Link and node failures may have more serious consequences when the mean load is optimized to a higher level, which leaves less unused capacity available to redirect the traffic.

Regarding longer paths, we experienced that nearly optimum path designs can be found with only few deviations from the shortest paths. Constraints on the number of hops or on link weights can be included in the optimization pro­ cess in order to prevent paths from violating delay bounds. Full exploitation of the traffic engineering gain may put QoS objectives at risk and a compromise between high resource utilization and QoS demands has to be found.

Conclusion The steady increase of Internet traffic volume demands for an ongoing scalable expansion process for ISP platforms where the load on the links is adjusted in a tradeoff between QoS demands and cost effective high utilization levels. Therefore upper bounds on the link utilization are derived from dimensioning rules regarding traffic profiles and QoS constraints. Since a sharp QoS degradation is expected in excess of a critical link utilization, network planning has to include forecasts to ensure QoS through timely upgrades of the topology. Statistical multiplexing has a smoothing effect on short term variability of aggregated traffic, whereas the daily profiles and long term growth factors are more variable and thus less predictable. Optimization tools for load balancing and traffic engineering can stabilize the throughput a network wide view, when a fine granular control of resource usage is enabled by directing explicit traffic paths through the network. The flexibility to redistribute imbalance of load in parts of a network is most valuable after traffic shifts and topology changes as well as in the planning

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Network Planning and Dimensioning for Broadband Access to the Internet

process by evaluating and optimizing topology design alternatives. The broadening spectrum of applications steadily changes the Internet traffic composition and poses new challenges in a trend towards broadband real time services. Despite a tremendous growth over recent years, the bandwidth currently available on ISP platforms is still far from being able to satisfy all demands of broadband applications especially for a widespread usage of video in HDTV quality. Even if traffic engineering has reached an advanced stage for broadband Internet platforms, mobile and wireless networks require even enhanced methods. New routing schemes are currently under study for unreliable environments e.g. in sensor networks with power saving nodes. The Internet standardization has formed working groups on routing over low power and lossy networks and mobile ad hoc networks addressing this area <www.ietf.org/html.charters/roll-charter.html>, . Traffic and network management will develop to cope with the challenges in heterogeneous domains of next generation networks.

References [1] Australian Bureau of Statistics, Internet activity, Latest issue (2007) <www.abs.gov.au/ AUSSTATS/[email protected]/Lookup/Main+Features1 Mar%202007?OpenDocument> [2] H. van den Berg, M. Mandjes, R. van de Meent, A. Pras, F. Roijers and P. Venemans, QoSaware bandwidth provisioning for IP backbone links, Computer Networks 50 (2006) 631-647 [3] K. Cho, K. Fukuda, H. Esaki, A. Kato, The impact and implications of the growth in residential user-to-user traffic, ACM Sigcomm Conf., Pisa (2006) <www.acm.org/sigs/sigcomm/ sigcomm2006> [4] Cisco Systems, Global IP traffic forecast and methodology, White paper,

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[5] DSL-Forum, <www.dslforum.org/dslnews/ pdfs/YE06_Release.pdf> [6] EURESCOM, Traffic modelling for the new wireless services (TRAWIS) Eurescom study program P1443 (2004) 1-38 [7] European Telecommunications Standards Institute (ETSI): Universal mobile telecommunication system (UMTS) – QoS concept and architecture, TS 123 107 / 3GPP TS 23.107 (2002) 1-37 [8] F. Hartleb and G. Haßlinger, Comparison of link dimensioning methods for TCP/IP networks, Proc. IEEE GLOBECOM, (2001) 2240-47 [9] G. Haßlinger, Quality-of-service analysis for statistical multiplexing with Gaussian and autoregressive input modeling, Telecommunication Systems 16 (2001) 315-334 [10] G. Haßlinger, J. Mende, R. Geib, T. Beckhaus and F. Hartleb: Measurement and characteristics of aggregated traffic in broadband access networks, Proc. 20. Internat. Teletraffic Congress, Ottawa, Canada, Springer, LNCS 4516 (2007) 998-1010 [11] G. Haßlinger, S. Schnitter and M. Franzke, The Efficiency of Traffic Engineering with Regard to Failure Resilience, Telecommunication Systems Vol. 29/2, Springer (2005) 109-130 [12] S. Kempken and W. Luther, Modeling of H.264 high definition video traffic using discrete time semi-Markov processes, Proc. 20. International Tele­traffic Congress, Ottawa, Canada, Springer, LNCS 4516 (2007) 42-53 [13] W. Leland, M.S. Taqqu, W. Willinger and D. Wilson: On the self-similar nature of Ethernet traffic, IEEE/ACM Trans. on Networking 2 (1994) 1-15

Network Planning and Dimensioning for Broadband Access to the Internet

[14] Multiprotocol Label Switching, IETF Working group <www.ietf.org/html.charters/mplscharter.html> [15] A. Odlyzko, Internet traffic growth: Sources and implications, Proc. SPIE Vol. 5247 (2003) 1-15 [16] Office of the Telecommunications Authority (OFTA) of the Hong Kong Special Administrative Region, Statistics of Internet Traffic Volume (Customer Access via Broadband Networks) (2008) <www.ofta.gov.hk/en/index.html> [17] W. Schmitz, New telecommunication applications and their impact on network platforms - Future of information technology, Proc. 50th anniversary Informationstechnische Gesellschaft ITG, Frankfurt, Germany (2004) 61-68 [18] P. Seeling, F. Fitzek, and M. Reisslein, Video Traces for Network Performance Evaluation, Springer (2006) [19] B. Staehle, A. Binzenhöfer D. Schlosser and B. Boder, Quantifying the influence of network conditions on the service quality experienced by a thin client user, Proc. 14. Conf. on Measurement, Modeling and Evaluation of Comp. and Comm. Systems (MMB), Dortmund, Germany (2008) 173-187 [20] University of Minnesota, MINTS: Minnesota Internet traffic studies

Key terms Buffers in Communication Networks: Buffers temporary can store data in terminals and switching systems of communication networks. When data is arriving faster than it can be processed then buffering is useful in order to avoid dropping a part of it. On the other hand, buffers in network elements introduce additional delay

which limits their efficiency for real time data transfers. Sender buffers help to reduce the variability of source traffic profiles and may transform a variable rate input stream into a constant rate output. In terminals, buffers are necessary to adjust different delays (delay jitter) of received data units for real time service and to hold it available until the play out time as well as for reordering out of sequence packets for transport protocols like TCP. Qual it y of Ser v ice/Qual it y of Experience:Quality of Service (QoS) and quality of experience (QoE) measure how much a telecommunication service achieves the expectations of the users. Quality of service introduces performance criteria for data delivery in transmission networks, with regard to throughput, delay, delay jitter and availability as main parameters. Quality of experience directly expresses the view of the user and determines the influence of QoS parameters on the user satisfaction. Methods to evaluate user satisfaction on a scale for the mean opinion score (MOS) are partly standardized e.g. for telephony and partly under research e.g. for video. Statistical Multiplexing: Statistical multiplexing is performed by switching systems in communication networks that merge data packets from multiple input lines and forward them to multiple outputs in a first come first serve or other scheduling discipline. In this way, many data flows can share capacity on a common transmission path. The aggregation of flows in a multiplexer is governed by statistical laws, such that the entire flow usually shows a smoothed rate variability as compared to single flow components. Traffic Engineering: Traffic engineering covers all measures to optimize and control traffic flows in a telecommunication network in order to ensure a maximum throughput and a sufficient QoS level. It is a part of the network planning, operation and management process of an ISP.

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Concepts for dimensioning, admission control, differentiation of services and failure resilience are included which should ensure a well balanced load level for good performance in normal operation and should keep important services available even in relevant failure scenarios.

source and destination as well as the same type of service marked in the packet headers. The TCP protocol initiates and terminates a flow by setting up and closing a connection in a handshake with the receiver, whereas UDP spontaneously starts and stops to send packets and flows.

Traffic Flow: A traffic flow carries data that is exchanged between the terminals during a communication service. In addition to unidirectional flows from a sender to a receiver, multicast or broadcast flows distribute data from a source to many destinations via splitting points in switching nodes of the network. Traffic flows on the Internet are transferred as a sequence of IP packets with protocol headers being added to the payload data to facilitate routing and delivery through the network. Internet standardization refers to an IP flow as a collection of successive packets with the same IP addresses and transport layer ports for

Traffic Profiles: Traffic profiles in communication networks refer to the mean rate and the variability of the traffic rate over time. Applications on the Internet generate their specific source traffic profiles, from which they may be classified as narrow- or broadband, constant bit rate or variable rate. Telephony and voice over IP differs in the traffic characteristic from video streaming and background data transfers, such that properties of source traffic profiles can be used to classify the corresponding application type. Traffic profiles are also measured for aggregated traffic on transmission links.

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Chapter LV

Overlay Networks:

New Techniques for Global Service and Network Provisioning Gerhard Haßlinger T-Systems, Germany

Abstract Service and content delivery over the Internet is currently supported by overlay architectures of different types. There is a trend towards distributed computing and service creation in peer-to-peer and grid networks, which are able to overcome performance bottlenecks of client server architectures. Overlays are deployed for single applications or as multi purpose infrastructure for communities with focus on their special demands. Various overlay structures have also developed on lower network layers. The motivation for those overlays is to bridge or extend one networking technology on top of another in order to build common widespread platforms through heterogeneous telecommunication environments. We address such approaches especially within the standardization of Internet protocols (IP), where the main focus is on evolving techniques on higher layers.

1 Introduction: Overlay networks on different layers Overlays on the application layer have developed since the millennium via peer-to-peer protocols where file sharing and voice over IP (Skype) reached world wide popularity. On lower protocol

layers, virtual local area networks (VLAN) and virtual private networks (VPN) are well known solution in order to group users communities together by a logical network topology on top of Ethernet or other technologies. The Internet engineering task force (IETF) devoted a considerable part of standardization work to transport mechanisms for support of different platforms over

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Overlay Networks

the Internet (IP) and generalized multi­protocol label switching (G-MPLS) networks. IETF working groups e.g. on pseudo wire emulation edge to edge (PWE3) have defined tunnelling mechanisms to bridge traffic from various platforms over IP including Ethernet and even synchronized transmission for telephony. Other working groups on virtual private networks within different layers (L1-, L2-, L3VPN) extend the basic mechanisms to build overlay networks including virtual private LAN services (VPLS), virtual circuit (VC) emulation etc. based on the previously defined tunnelling mechanisms. On the application layer, peer-to-peer (P2P) networking overlays became popular in telecommunication through file-sharing applications, which fundamentally changed the traffic profile on the Internet since the millennium. Two main advantages of the peer-to-peer principle as compared to client-server systems are • A highly efficient distribution of data over the Internet with scalability even for spontaneous requests from millions of users to large files and • The opportunity to build overlay networks to launch new Internet services around the globe with a minimum of own server and network infrastructure to maintain control. P2P overlays on the Internet have a profound impact on the business of Internet service providers (ISPs) by making new services available in a short time. Together with the penetration of broadband access, P2P services mark a new phase of Internet evolution with major shifts in technology, service architecture and business models for service providers. Besides file sharing, voice over IP and gaming via P2P systems also have reached populations counting in millions and further applications are expected to make widespread use of pure P2P techniques or hybrid forms combining P2P with server architectures.

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Functions with a high consumption of system resources and performance requirements in computation power, storage or bandwidth for data exchange can benefit most from P2P and other overlay structures. Overlay networks generate their own traffic pattern and usually introduce explicit or implicit routing functions e.g. by the selection process of sources for downloads in P2P networks. The data throughput in popular P2P networks is maximized by elaborate techniques including parallel multisource downloads and incentives to motivate users to make upload capacity available. But transmission paths in P2P overlays are often observed to be suboptimal, since data flows are routed more or less independent of the underlying transport network topology. As an alternative, content delivery networks (CDNs) have developed from pure content provisioning to support a broadening range of IP services. The advantage of P2P networks can be seen in the opportunity to move operational costs for a service from central servers to the equipment of the users. This facilitates the global launch of new services at low price or for free. On the other hand, security, reliability and control issues are more difficult to handle in a distributed architecture on user equipment. CDNs can enforce full control over the offered content and services at the cost of infrastructure to be installed and maintained within the network. In addition, operational ISPs and telecommunications network providers offer value-added overlay services in a broadband environment. Therefore at least three types of overlays are relevant above the network layer: • Content distribution networks (CDNs) as global overlays on Internet servers supporting popular Web sites, • Peer-to-peer applications building overlay networks on the terminals of the users, • And overlays within the architecture of a network or service provider, utilizing own infrastructure including caches, multi-

Overlay Networks

/broadcasting or servers in the framework of next generation networks. These alternative overlays will compete in building a basis for future Internet services, where different approaches may achieve acceptance for one service or another, depending on how efficient the overlay type can meet all relevant demands at lowest possible costs. Among the prerequisites for successful overlays, which decide about which types of overlays will prevail to carry a specific set of applications are • Efficient search functionality, • Reliability, replication schemes and security measures, • Scalability for handling a large number of users, a large amount of data and further network resources, • Performance and quality of service of the solution in a trade off with costs of the resources, • Charging principles and incentives for business applications, that are acceptable for all involved parties. After addressing overlays due to IETF standardization in Section 3, we examine the development and the efficiency of peer-to-peer content distribution in Sections 4 and 5. Cross layer aspects and the potential for path optimization in the underlying network layer are discussed in Section 6. Finally, Section 7 gives a comparison to content delivery networks (CDN).

2 Internet standardization for overlays on lower layers Before considering overlays above the network layer, i.e. the IP layer in the Internet, we first address overlays on lower layers combining technologies on the network, the data link and partly

on the physical layer. A closer look on work by the Internet engineering task force (IETF) reveals a long history in standardization of overlays around IP. As a first step, a point-to-point tunnel can be set up on a network infrastructure connecting two interfaces attached to networks of a different type at both ends. In this way, different networks protocols can be bridged from access points over the Internet as illustrated in Figure 1. The data of the attached networks is encapsulated and segmented into IP packets when entering the tunnel. After transport over the IP network they are reassembled at the tunnel end to regain the data format valid in the attached networks. Some IETF working groups are mainly focused on tunnelling mechanisms, e.g. the pseudo wire emulation edge to edge (PWE3) working group. The Web site <www.ietf.org/html.charters/wg-dir. html> provides a steadily updated view on IETF working group charters. In addition, network structures are established as overlays over IP and (G-)MPLS (generalized multiprotocol label switching) networks, which make use of a subset of the core nodes and links. Working groups on virtual private networks (VPNs) have set standards in this area and spread their activity on multiple layers (L1-, L2-, L3VPN on layers 1-3). The number of RFC standardization documents dealing with overlays of various kind is well beyond 250. Usually such work is indicated in a title of the form “protocol or technology X over Y”. Some typical examples are listed in Table 1. It seems to start with the original role of the Internet of interconnecting Ethernets as the prevalent technology in local area networks. The Internet protocol (IP) is enabled to run over Ethernets and in this way expands into the local domain [13]. This includes specification of the mutual correspondence of IP and Ethernet MAC (medium access control) addresses and gateway functions for converting packet formats. Most data in IP networks is transported in packets of 1500 Byte due to the maximum size to be encapsulated

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well beyond 250. Usually such work is indicated in a title of the form “protocol or technology X over Y”. Some typical examples are listed in Table 1. It seems to start with the original role of the Internet of interconnecting Ethernets as the prevalent technology in local area networks. The Internet protocol (IP) is enabled to run over Ethernets and in this way expands into the local domain [13]. This includes specification of the mutual correspondence of IP and Ethernet MAC (medium access control) addresses and gateway functions for converting packet formats. Most data in IP networks is transported in packets of 1500 Byte due to the maximum size to be encapsulated within Ethernet frames.

Figure 1. Tunnels and overlay networks on the Internet

P el; nn Tu

since transmission of IP or MPLS packets is subject to variable delays caused by temporal buffering in routers. Then a dejitter buffer has to compensate for delay variability in gateways from the packet to the synchronous network. Such solutions are desirable for connecting other network types at IP, (G-)MPLS- or other packet switching network multiple locations over the Internet, but the efficiency and usability of reversed overlay relationships are not guaranteed in all situations. In addition, IP-in-IP encapsulation or tunnelFigure 1: Tunnels and overlay networks on the Internet ling becomes useful in several scenarios, e.g., IP packets are also transported on other link layer technologies for wide area networks, including optical neto ud se

ire W

works [15] (WDM: wavelength division multiplexing, SONET: synchronous optical networks, SDH: synchronous digital hierarchy). Support by corresponding standardization activity is often done in collaboration between the IETF and other fora or standardization bodies for different link layer technologies.

within Ethernet frames. • In mobile networks, when data is first sent IP packets are also transported on other link to a home agent and then forwarded from layer technologies for wide area networks, includthe home agent to the current location of the ing optical networks [15] (WDM: wavelength divimobile node using a new care-of address sion multiplexing, SONET: synchronous optical or the IP address of a foreign agent of the Table 1: Some IETF standard documents on overlays (RFC: request for comment) networks, SDH: synchronous digital hierarchy). hosting network, RFC 895 [13] Standard for the transmission of IP datagrams over experimental Ethernet (IEEE 802) networks Support by corresponding activity RFC 4717, 4619, Encapsulation for Transport of ATM, standardization Frame Relay, PPP (point-to-point protocol), HDLC • For transport of different protocol variants, 4618, 4448 [12] (high level data link control), Ethernet over MPLS is often done in collaboration between the IETF for security and other purpose or for carryRFC 3717 [15] IP over Optical Networks: A Framework RFC 4842 [11] Opticalor Network/Synchronous Digital Hierarchy (SONET/SDH) andSynchronous other fora standardization bodies for dif-Circuit Emulaing IPv6 packets over IPv4 networks [4]. tion over Packet (CEP) ferent link layer technologies. RFC 3251 [14] Electricity over IP RFC 4817 [21] Encapsulation over Layer 2 Tunneling Protocol defined tunSince theof MPLS millennium, the IETF Overlay and tunnelling techniques add comRFC 4906 [12] Transport of Layer 2 Frames over MPLS nels and overlays on top of IP and MPLS packet plexity to the protocol stack and increase the overRFC 4798 [4] Connecting IPv6 Islands over IPv4 MPLS Using IPv6 Provider Edge Routers RFC 5087 [17] Time Division over IP in Figure 1 [11][12][17]. networks asMultiplexing illustrated head due to additional headers in transmission. This becomes challenging when synchronous and There is often a controversial discussion about connection oriented techniques are transported appropriate use cases and not all options gain over connectionless packet networks [11][17], wide spread usage as expressed in the document Since the millennium, the IETF defined tunnels and overlays on top of IP and MPLS packet networks as illustrated in Figure 1 [11][12][17]. This becomes challenging when synchronous and connection oriented techniques are transported over connectionless packet networks [11][17], since transmission of IP or MPLS packets is subject to variable delays caused by temporal buffering in routers. Then a dejitter buffer has to compensate for delay variability in gateways from the packet to the synchronous network. Such solutions are desirable for connecting other network types at multiple locations over the Internet, but the efficiency and usability of reversed overlay relationships are not guaranteed in all situations.

Table 1. Some IETF standard documents on overlays (RFC: request for comment)

870

RFC 895 [13]

Standard for the transmission of IP datagrams over experimental Ethernet (IEEE 802) networks

RFC 4717, 4619, 4618, 4448 [12]

Encapsulation for Transport of ATM, Frame Relay, PPP (point-to-point protocol), HDLC (high level data link control), Ethernet over MPLS

RFC 3717 [15]

IP over Optical Networks: A Framework

RFC 4842 [11]

Synchronous Optical Network/Synchronous Digital Hierarchy (SONET/ SDH) Circuit Emulation over Packet (CEP)

RFC 3251 [14]

Electricity over IP 

RFC 4817 [21]

Encapsulation of MPLS over Layer 2 Tunneling Protocol

RFC 4906 [12]

Transport of Layer 2 Frames over MPLS

RFC 4798 [4]

Connecting IPv6 Islands over IPv4 MPLS Using IPv6 Provider Edge Routers

RFC 5087 [17]

Time Division Multiplexing over IP

Overlay Networks

on electricity over IP [14]. The latter does not refer to powerline or extend power supply integrated in Ethernet, but has deliberately chosen April 1. as editorial date. Referring to a draft version of the SDH/SONET over IP/MPLS work, which was discussed since 2002 and recently entered the proposed standards track [11], the abstract of [14] comments “Readers of the previous work have been observed scratching their heads and muttering: What next?”. In addition to funny suggestions in [14], the current discussion on TCP over UDP <www.ietf.org/proceedings/08mar/ slides/mmusic-1.pdf> seems to be another answer, although driven by serious concerns to overcome NAT (network address translation) traversals via UDP, which is often impossible with TCP, while preserving the TCP overload and error control on top. Other standardization bodies including 3GPP <www.3gpp.org> and ETSI TISPAN are partly extending IETF work for next generation networks (NGN) by setting up overlays for end-to-end services via different transport media in convergent fixed and mobile networks. The IP multimedia subsystem (IMS) is a well known overlay standard relying on the session initiation protocol (SIP) by the IETF.

3 Peer-to-peer networking: Overlays on the users’ terminal equipment Since the millennium, peer-to-peer (P2P) networking has shown its potential for efficient content distribution and for unleashing idle resources to form scalable and resilient overlays. Peer-to-peer protocols have established popular file sharing and voice over IP (VoIP) applications on a global scale, which offer replicated data distribution schemes and scalable adaptation to the demands at a fraction of the cost of traditional server based approaches. P2P overlays on the end systems of the users give new opportunities for

worldwide service provisioning at a minimum of own infrastructure. In recent years, file sharing often contributes 50% - 80% of the traffic volume on broadband access platforms in Europe and around the world [8]. Although unresolved legal issues still leave an uncertain future for file sharing as a major part of ongoing P2P activity, the spectrum of P2P applications is steadily broadening towards secured research and business applications. The P2P-based Skype solution has become the most popular voice over IP network within less than two years and new P2P approaches are evolving for audio and video streaming, IP-TV, online gaming, cooperative work tools etc. Table 2 shows a brief history of the appearance of some main P2P applications, starting with Seti@Home as a network to make computation power available for a scientific project analyzing extraterrestrial signals under central control. New P2P services are established partly without own server and network infrastructure or in hybrid architectures with a minimum of central server functions in order to maintain control. Ongoing research in P2P networking addresses security functions [7], overlay optimization, search algorithms via distributed hash tables [18] or unstructured search approaches on distributed database systems [20]. Despite of steadily advancing features built into current P2P applications, many of the most Table 2. Timeline of emerging popular P2P protocols and developments 1999 2000 2001 2002

2005

2008

Grid Computing: Seti@Home File Sharing: Napster Gnutella eDonkey, FastTrack (Kazaa) etc. BitTorrent VoIP: Skype Support for games, pod casting, video streaming, P2P SIP, mobile P2P, etc.

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Overlay Networks

popular P2P networks seem to be initially launched by small groups of software developers or even by a single person [3], without much involvement of larger players in telecommunication or research institutes. Therefore standardization of peer-topeer systems is at an early and still premature stage. A working group on peer-to-peer session initiation (P2P-SIP) has been formed by the IETF for locating users and resources for SIP-based communications and presence in a distributed scheme in addition to the server oriented SIP (session initiation protocol) approach. Application types that are most likely to benefit from peer-to-peer systems are gaming, eLearning, support for enterprises and small communities with extensions into mobile and wireless networks. • Online gaming and eLearning: In both cases, there are similar demands to distribute and update large software packages and to support online activity in multi user games and interactive learning scenarios. The Blizzard gaming platform, e.g., makes use of the Bit­Torrent file sharing protocol for soft­ware down­loads <www.blizzard. co.uk/wow/faq/bittorrent.shtml>. • Support for small communities and enterprises: P2P overlays can give access to content and multimedia services according to the specific demands of a community or company including secured and authorized access within closed user groups. • Wireless and mobile networks: Fixed mobile convergence is a challenging environment for P2P systems. Links in mobile and wireless networks have smaller bandwidths and are less reliable. There is a higher churn rate due to changing access conditions of the nodes. Nevertheless, P2P networks have been developed to adapt to unreliable and variable network conditions and provide a promising alternative for ad hoc and selforganizing networks.

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• IP-TV, streaming and multicast services: Among recent developments, P2P based video distribution is adopted by major broadcasting stations, e.g., in the BBC iPlayer , which may be seen a pre-stage of P2P-based Internet television (IP-TV). The BBC iPlayer makes parts of the TV and radio program available for one week after the broadcasting date including digital rights management (DRM) and security enforcement. The volume of popular unlicensed multimedia content on the Internet is also increasing. There is a variety of providers of open platforms for special purpose with content of various types. Search engine operators also support open content provisioning within their infrastructure. In this environment, peer-to-peer approaches must compete on even grounds with other methods of content distribution. Viability and usability of peer-to-peer networks is measured through technological and economical efficiency and competitiveness.

4 Efficiency of P2P content distribution Analysis of the Delivery Time for Homogeneous Peers and Unique Transfer Times Next, we investigate P2P content delivery schemes in more detail to get insight into the structures and features required to distribute data volumes over a large community in about the same time as for a single end-to-end data transfer. Content distribution has developed to cover many multimedia applications with prevalent one way transmission from Web browsing to video streaming. We make some simplifying assumptions focusing on a homogeneous overlay network with the same bandwidth B being available at each peer.

Overlay Networks

mission time for a data chunk is (C / K + P ) / B with regard to some overhead P for additional information e.g. a hash identifier being added for unique identification of a chunk. The overhead P may cover connection setup times or other delays occurring between successive chunk transfers. We assume an unrestricted full mesh of connections between N peers including a source holding the content from the start and the other peers waiting and willing to cooperate in the content distribution. The analysis is done for N = 2M. The source trans­mits the complete series of chunks one by one choosing different destinations. After the first chunk has been received by a peer, this peer will forward it in parallel to further transfers from the source. As soon as a peer has received at least one chunk, it is assumed to upload a chunk in each step. In a first phase, chunks are always transmitted to peers who still haven’t got one. In this way, the number of peers that received a chunk is growing to 2m after m transmission steps. Figure 2 illustrates the progress after m chunk transfer times in an example with 24 peers. For N = 2M, the first chunk is completely distributed after M + 1 steps. At the same time, the second chunk is already available at half of the peers, while the (M+1)-th chunk has just been delivered once from the source. In general, the delivery of

We presume unique end-to-end connectivity between peers without considering the underlying network structure in detail. The bandwidth B is bi-directional and can be independently used for up- and down­loading in parallel. In fact, ADSL broadband access is prevailingly deployed with asymmetrical up- and downstream speed, but since current P2P protocols enforce a symmetrical traffic in both directions [8], we consider the upstream access capacity as the bottleneck for both directions. Initially, the content of size C is located on and provided by a source as one of the peers. From the start of the content distribution, we consider N peers who want to get the content and we presume that they build a cooperative P2P subnet to forward the content to each peer without involving others. We assume that the content of size C is subdivided into K data chunks of equal size. The number K of data units is an important parameter for the performance of delivery, since the subdivision into small data portions enables flexible parallel transfers. Each data chunk as well as complete files are uniquely marked by hash identifiers. Once a peer has completely received a chunk, it can start to forward it to other peers. Upload of received data is enforced as soon as possible by current file sharing protocols [3]. The trans-

Figure 2. Idealized scenario for efficient peer-to-peer content distribution Source P1

Network of peers P1Pj...interested PN interested in the data Network of peers in the data setD P9 … P16 … P2 P3 P4 P5 1

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chunk k is completed in step M+k, when again the (M+k)-th chunk has just been transferred once. The delivery process can be made periodical from the 2M-th step onwards, such that the ( j+M)-th chunk is transmitted over the same peer-to-peer connection as the j-th chunk M steps ahead. There are many appropriate schemes for choosing the destinations for delivery in each step as in Figure 2, which have to ensure that a chunk isn’t transferred twice to the same destination. Thus the content can be for­warded from a source within M+K chunk transfer times to N = 2M other peers in a full mesh P2P network. It can be shown that the same delivery time T is sufficient for 2(M – 1) < N ≤ 2M and we can conclude T = ( log2(N ) + K ) (C /K + P ) / B = [1+ M /K + ( M + K) P/C ] C / B where (C /K + P ) /B is the time for one chunk transfer step and log2(N ) + K = M + K is the number of steps. Usually, we can assume P/C to be small, since a few header or trailer bytes including a hash value should be sufficient as overhead P, whereas the content is often much larger in the MB or GB range. In addition, M can be bounded even in large P2P networks by M ≤ 25 to include up to 25 N = 2 > 33 million peers. Then for M ≤ 25 and –4 P/C < 3×10 we conclude that K = 250 chunks are always sufficient to obtain M /K ≤ 0.1 and (M+K) P/C ≤ 0.1, yielding T < 1.2 C/B. Thus the delivery time T of content over a large P2P network can be kept close to the transfer time C/B of the content to a single destination.

investigated. Since no overhead per data chunk is considered in [1], their results are in accordance with the previous analysis for P = 0. Comparing content distribution via chain, tree and full mesh structures for homogeneous peers, the mesh achieves a close to optimum performance under fairly general conditions. The restriction to a tree suffers from the fact, that the upload capacity of the leafs is not utilized, leaving only a fraction 1/h of the capacity in the network for the distribution process, and therefore slowing down the delivery by about the same factor. In all cases, a subdivision of the content into small chunks essentially reduces the delay. The performance of the linear chain is essentially affected by additional overhead or delays per chunk and depends on the number of chunks, which has to be optimized with regard to the content size and the length of the chain. For the performance of the tree and mesh distribution, the overhead per chunk is less important and a moderate number of chunks K = 250 is always sufficient. With regard to fault tolerance, an unrestricted P2P mesh offers alternative paths to bypass failed links and nodes, whereas a linear or tree structure offers only a single source to destination path. In fact, only a part of the full mesh connections is required for content distribution. In each transfer step, N parallel connections are utilized. Since the delivery process can be made periodical after log2(N ) steps, only N log2(N ) out of N (N – 1) peer-to-peer connections are required, i.e. a partial mesh of no more than N log2(N ) connections already can achieve optimum performance.

Comparison to Analytic Work Including Delivery via a Tree or Linear Chain

Discussion of Content Delivery in Generalized Environment of Realistic Scenarios for Current P2P Protocols

A more detailed performance analysis is given by [1] including heterogeneous peers. In addition to transmission over a full mesh, cases of a delivery over a tree structure and in a linear chain are also

In fact, the previous analysis makes some idealistic assumptions leading to a deterministic and synchronized distribution in a predefined schedule. Popular peer-to-peer networks have to adapt to

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different delays per data transfer depending on the length of transmission paths between peers in the underlying network. A source decides to upload data chunks based on incoming requests and a local prioritization scheme rather than on a network wide synchronized schedule. Nevertheless, the self-orga­ni­­zing distribution of current P2P protocols is flexible enough to closely approach the optimum performance of the analyzed deterministic scheme. After the initial phase, the delivery in a mesh structure exhausts almost the complete access bandwidth of homogeneous peers. Therefore only the first M steps could be further improved. In the initial phase, it would be helpful to have a source or peers with larger upload speed involved. A powerful source peer with 2m -fold bandwidth can distribute 2m different chunks to 2m peers in parallel in a single step and thus would skip m–1 steps. But only a small fraction m/(M+K) of time can be saved in this way. Multiple uploads from the same source in parallel do not improve the performance for homogeneous peers. Simul­taneous uploads with bandwidth B / n shared among n chunks of equal size C are all completed after a delay of nC/B. For sequential uploads with bandwidth B, chunks are delivered earlier after C/B, 2C /B, 3C /B, …, which is favourable in the starting phase to supply all peers with a chunk and to make their upload capacity available as fast as possible. However, multiple up- and downloads in parallel are essential in communication between heterogeneous peers equipped with different access speeds. When many peers have a unique basic access speed and there are some peers with higher, e.g. n-fold speed, then it is easy to integrate them by subdividing their speed into n up- and downloads at unique speed in parallel. With a single transmission per peer, it would be difficult to fully utilize peers at different bandwidths due to the restrictions for transmitting between pairs of almost equal speed.

An extension of the performance bounds and estimations to heterogeneous P2P networks is more complex, but surely relevant, since different access speeds are offered for residential users and some very powerful hosts are often involved in P2P networks. Although multi source downloads are appropriate to adapt to the heterogeneity, the delivery time for content of size C starting from a source with bandwidth BSource, is obviously limited by C /BSource as a bottleneck at the source. When the data is available in the P2P network and distributed over many peers, then the access speed of most powerful hosts among the peers can be exploited. More generally, we may distinguish several classes of peers at different access speed but with the same speed within each class. Then a class of high speed peers including the source can be viewed as a homogeneous subnet, whose delivery time is determined by the access speed of this class, even if the complete P2P network includes many peers of lower speed. In addition, the peers with lower access speed can profit from faster peers, especially in case of asymmetrical access (ADSL). On the whole, bounds on the delivery time to all peers can be set up in terms of the mean upload speed per peer, since the upstream is assumed as the bottleneck in asymmetrical access, where classes of peers with higher speed may finish a download earlier than peers with smaller access bandwidth. From the view of each peer, the access speed of the peer can impose a bottleneck, as well as the upload speed of the source, if the content is only available from a source and not yet distributed over the network. Involving more peers from outside of the subnet also wouldn’t improve the main distribution phase, since the bandwidth of the peers is already exhausted by the distribution scheme as suggested by Figure 2 within the subnet of all peers interested in the content. For asymmetrical ADSL access with a ratio R of download ÷ upload capacity the situation is different, since then the download

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Overlay Networks

capacity can only be exploited by R peers uploading in parallel to the same destination. Solutions for efficient content distribution apply in a similar way to non-real time as well as real-time applications, provided that real time data, e.g. a video stream,+ is again subdivided into data chunks of suitable size.

5 Transport paths and cross layer aspects In the previous section, we focused on the application layer, where P2P overlays are shown to be highly efficient for content distribution and in providing a welcome opportunity to launch services at low infrastructure and development costs. However, the advantage of becoming independent from the transport and network layer is achieved on account of some overhead for an additional protocol layer. P2P protocols establish their own routing schemes by selecting down­load sources via an inherent search scheme, including “hello” mechanisms to verify the availability of peers. When comparing the message exchange for downloads via the eDonkey and BitTorrent protocol, we experience a messaging over­head of 10-20% considering the ratio of the complete transferred

data volume during a download to the size of the file. For small files there is more overhead. The first version of the Gnutella peer-to-peer network, that partly replaced Napster after shutdown, wasn’t scalable because of flooding many search messages through large parts of the network [10]. Another major performance issue is the length of paths for data transfers, i.e. the hop distance from source to destination. In P2P networks, frequently referenced data is replicated manifold according to the demands and becomes available from many sources. So, there is a potential to optimize the transfer paths by preferring the nearest sources. In this way, transmission delays and thus the user perceived QoS can be improved as well as the resource usage of network providers, avoiding unnecessary long paths through the backbone or on expensive peering and intercontinental links. Figure 3 illustrates a usual topology of broadband access networks, where tree-shaped access areas are attached to edge routers of the backbone at points of presence (PoPs). Considering large provider networks serving millions of subscribers, it can be expected that a majority of the data of a global file sharing network can already be found to be replicated on the same ISP platform and often in the same access region of the P2P downloader. This especially holds for highly popular and referenced data, since the major

there is more overhead. The first version of the Gnutella peer-to-peer network, that partly replaced Napster after

Figure 3. shutdown, Usual structure of broadband access wasn’t scalable because of flooding manyplatforms search messages through large parts of the network [10]. Users

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Figure 3: Usual structure of broadband access platforms

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Another major performance issue is the length of paths for data transfers, i.e. the hop distance from source to destination. In P2P networks, frequently referenced data is replicated manifold according to the demands and becomes available from many sources. So, there is a potential to optimize the transfer paths by preferring the nearest sources. In this way, transmission delays and thus the user perceived QoS can be improved as well as the resource usage of network providers, avoiding unnecessary long paths through the backbone or on expensive

Overlay Networks

portion of down­loads is addressed to a small set of the currently most popular files. But peer-topeer networks have no direct knowledge of the underlying IP network structure. The fact that the response time and availability of the peer nodes are related to the length of transmission paths on the network layer gives some preference for shorter paths. But this effect is less relevant than structures in the overlay, which are imposed through server or super node locations or communities separated by language and social environments. The distribution of source locations offered by the eDonkey network for downloading German and English content has been investigated from destinations in Germany with results shown in Figure 4. It is not surprising, that 78% of the sources for German content were also located in Germany, whereas most (83%) of the English content is transferred from peers in other countries, which puts load on backbone and peering links of the network providers. Similar experience for locality of sources due to language has been made for file-sharing in France [9]. Especially the figures for English content downloaded in Germany demonstrate the global distribution of source locations, resulting in long download paths over intercontinental links and causing long transmission delays. Thus network providers as well as the users and thus the P2P protocols should be interested in preferring peers

close to the destination. Since the location of peers can be estimated from their IP address at least with regard to their corresponding autonomous system and network operator, it is feasible to do better. This could be achieved by improved source selection mechanisms in the P2P protocol or by using caches for serving downloads in the proximity. There are several proposals for cooperation between network providers and P2P protocols for file sharing [1][5][6][22]. Cooperative approaches [1][22] would have the highest potential for efficient solutions by selecting appropriate sources and including caches or even CDN-like architectures [5][6] to support local content distribution. But file sharers, and thus the protocols they use, usually try to avoid that their IP addresses are looked up and processed due to special policies of third parties, even for the goal of optimizing their performance.

6 Content delivery networks: Overlays embedded in the Internet structure Content delivery or distribution networks (CDNs) provide an alternative overlay structure within the network layer and thus within platforms of ISPs.

Figure 4. Sources for downloads to German sites in the eDonkey network and types of content [16] Sources in different countries for English content downloaded in Germany 78%

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17.3%

Others 70.9% 2.4%

Figure 4: Sources for downloads to German sites in the eDonkey network and types of content [16] Especially the figures for English content downloaded in Germany demonstrate the global distribution of source locations, resulting in long download paths over intercontinental links and causing long transmission delays. Thus network providers as well as the users and thus the P2P protocols should be interested in preferring peers close to the destination. Since the location of peers can be estimated from their IP address at least with regard to

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Overlay Networks

After a user contacts a Web site, which is supported within the CDN network, his request is redirected via a CDN overlay to a server in the near of the user. A performance study on Akamai’s CDN [19] reveals that a large hierarchical server farm is efficiently utilized to shorten the transmission paths. The solution includes frequent updating of the best path to a user based on measurement of the network and server performance. A backup path from another server is also prepared for failure resilience. In this way, CDNs offer advantages over P2P networks for optimized reliability and low delay as main QoS measures. Short transmission paths to globally distributed Web sites reduce traffic in the backbone and on expensive transatlantic links of network providers. Another advantage of content delivery networks is that content is stored in a controlled way on provider infrastructure whereas it is distributed over customers’ and users’ equipment in P2P networks. Although a secured and controlled access is also enabled for P2P using strong encryption methods, some content providers may still have more trust in securing valuable content on their own infrastructure. Search engines and the majority of popular Web sites have organized CDN support on their own or with the help of CDN providers like Akamai. Web caches provide another opportunity to optimize traffic paths. In principle, caches are efficient for P2P data since a high hit rate can Figure 5. Transfer paths via content distribution networks Hierarchical S WWW Server of a CDN Customer

... ... ...

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DNS Request

7 Summary and conclusions

erver Farm

Path Performance Measurement & Update Process

Backup Path

DNS Redirect

be expected and problems of outdated data as in classical Web caches are avoided because the P2P content is uniquely identified by hash values. Since October 2004, the eDonkey P2P network offers an option to use Web caches of network providers by disguising P2P downloads as usual HTTP Web browsing requests. Indeed, eDonkey downloads can be observed to partly originate from caches, but only to a small extend of less than 10% being indicated in the eDonkey performance statistics [16]. From the network provider’s view, the caching option for support of P2P networks remains ambiguous. While transfers from the cache take load away from the backbone and reduce off-net traffic, other downloads may continue without caching and may generate a higher total traffic load. The problem of also supporting the distribution of copyright infringing or other illegal content via caches or other techniques for efficient transport is known since the Internet became popular. But it has attracted much more attention and is pursued by various counteractions since file sharing networks have been made responsible for decreasing revenues for content providers in the music and film industry. Last not least, network providers have opportunities to build content distribution architectures using their own infrastructure e.g. via multicast for support of broadcast services. Usually this does not lead to global access but is often appropriate for regional services e.g. for IP-TV within a country or lingual community.

Internet Access User

Best Path

Overlays of various types are used to bridge heterogeneous networks to enable a seamless end-to-end service delivery. This becomes even more relevant in the current fixed/mobile convergence phase integrating wireless and mobile communication on different technologies with Internet access. A major advantage of overlays is their ability to provide new services or extend existing services

Overlay Networks

on top of an underlying infrastructure. Internet standardization by the IETF has made extensive use of tunnelling and overlay techniques. On the application layer, peer-to-peer networks establish overlays on terminal equipment of the users, offering global services with a minimum of own network infrastructure. Scalable and highly efficient delivery of large volumes of content to a large community of subscribers is characteristic for peer-to-peer networking. Content delivery networks (CDN) usually do a good job in optimizing transmission paths and corresponding delay by choosing the nearest server in their platform to contact each user. Network providers include overlay traffic in the planning and upgrade process of the network topology including mechanisms for load balancing. But in this way, inefficient routing on higher layers can only be partly reduced by optimization on lower layers. Overlays add to the number of layers in the communication protocol stack. As a consequence, they increase overhead and cross-layer inefficiency by repeating similar functions on several layers or, as a worst case, by employing functions on different layers, which are jarring with each other. Therefore overlays should be set up with implicit or explicit awareness of the underlying network structure. On the other hand, it is a challenging design question for future Internet architecture to avoid complex layering structure and at the same time to keep the flexibility to respond to new requirements and technical opportunities as the main motivation for the appearance of overlays of various type.

References [1] V. Aggrawal, A. Feldmann and C. Schneideler, Can ISPs and P2P users cooperate for improved performance? ACM SIGCOMM computer communications review 37/3 (2007) 31-40

[2] E. Biersack, D. Carra, R. Lo Cigno, P. Rodriguez and P. Felber, Overlay architectures for file distribution: Fundamental analysis for homogeneous & heterogeneous cases, Computer Networks 51 (2007) 901-917 [3] B. Cohen, Incentives build robustness in BitTorrent, (2003) [4] J. De Clercq, D. Ooms, S. Prevost and F. Le Faucheur, Connecting IPv6 Islands over IPv4 MPLS Using IPv6 Provider Edge Routers, IETF, RFC 4798 (2007) [5] M. Faycal and A. Serhrouchni, CAP: A context-aware P2P system, Proc. OTM’07, Springer LNCS 4806 (2007) 950-959 [6] R. Ferreira, A. Gramma and S. Jagannathan, Pletora: An efficient wide area storage system, Proc. HiCP’04, Springer LNCS 3296 (2004) 252261 [7] L. Gaspary, M. Barcellos, A. Detsch, R. Antunes, Flexible security in peer-to-peer applications: Enabling new opportunities beyond file sharing, Computer Networks 51 (2007) 47974815 [8] G. Hasslinger, ISP Platforms under a heavy peer-to-peer workload, Proc. Peer-to-Peer Systems and Applications, Eds.: R. Steinmetz and K. Wehrle, Springer LNCS 3485 (2005) 369-382 [9] G. Hasslinger, F. Guillemin, J. Ferreira and U. Halldorsson, The impact of peer-to-peer networking on network operators and Internet service providers, Eurescom study report P1553 (2005) <www.eurescom.eu/public/projects/P1500-series/p1553/> [10] D. Ilie, A. Popescu, Statistical models for Gnutella signaling traffic, Computer Networks 51 (2007) 4816-4835 [11] A. Malis, P. Pate, R. Cohen, Ed., D. Zelig, Synchronous Optical Network/Synchronous Digi-

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tal Hierarchy (SONET/SDH) Circuit Emulation over Packet (CEP), IETF, RFC 4842 (2007) [12] L. Martini et al., Encapsulation for Transport of ATM, Frame Relay, PPP, HDLC, Ethernet over MPLS, RFC 4717, 4619, 4618, 4448, 4906 (2006) [13] J. Postel, Standard for the transmission of IP datagrams over experimental Ethernet (IEEE 802) networks, IETF, RFC 895, 1042 (2005) [14] B. Rajagopalan, Electricity over IP, IETF, RFC 3251 (1.4.2002) [15] B. Rajagopalan, J. Luciani and D. Awduche, IP over Optical Networks: A Framework, IETF, RFC 3717 (2004) [16] J. Schroeder-Bernhardi, Analysis of the communication and traffic in P2P networks including Web caches, Diploma Thesis, Report KOM-D-260, Darmstadt Univ. of Tech. (2006) [17] Y(J). Stein, R. Shashoua, R. Insler, M. Anavi, Time Division Multiplexing over IP, IETF, RFC 5087 (2007) [18] I. Stoica et al., Chord: A scalable P2P lookup protocol, IEEE/ACM Trans. on Networking Vol. 11 (2003) 17-32 [19] A.-J. Su, D.R. Choffnes, A. Kuzmanovic and F.E. Bustamante, Drafting behind Akamai, ACM SIGCOMM, Pisa, Italy (2006) [20] W. Terpstra, J. Kangasharju, C. Leng and A. Buchmann, BubbleStorm: Resilient, probabilistic and exhaustive P2P search, Proc. ACM SIGCOMM, Kyoto, Japan (2007) 49-60 [21] M. Townsley, C. Pignataro, S. Wainner, T. Seely and J. Young, Encapsulation of MPLS over Layer 2 Tunneling Protocol Version 3, IETF, RFC 4817 (2007) [22] H. Xie, A. Krishnamurthy, A. Silberschatz and Y. Yang, P4P: Explicit communications for cooperative control between P2P and network pro-

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viders, <www.dcia.info/documents/P4P_Overview.pdf>

Key terms Cache: Caches provide storage within the network infrastructure of Internet service providers as well as for support of servers. Data transfers from remote sources can partly be abbreviated from a cache in the near of the destination, thus enabling optimized transfer paths in a similar way as done by CDNs. Content Delivery (or Distribution) Network (CDN): Content delivery networks provide support of popular Web sites or search engines in the Internet. They employ an overlay consisting of globally distributed server farms, which enables to optimize data transfer paths and transmission delays by choosing a server close to the location of the requesting user. Internet Engineering Task Force (IETF): The main technical standardization body for the Internet <www.ietf.org>. The IETF is a non-member organization open for individual volunteers to contribute to Internet protocol development. The IETF in organized in more than hundred working groups on current topics, holds three annual meetings with most of the work being available in Internet drafts and mailing list discussions. The IETF has conducted a lot of basic work for overlays in telecommunication on and around the network layer. Overlays: A popular method to put new services or technologies on top of an existing telecommunication network infrastructure. Peerto-peer networks are an example of an application layer overlay. The IETF and other standardization bodies have defined overlays on lower layers for many purposes between packet networks (IP, MPLS), Ethernet and synchronized networks for voice transmission. In this way, a standard

Overlay Networks

networking solution can be carried and thus extended over other networks or combined with them in a heterogeneous networking environment. Overlays add new layers to a communication architecture. Peer-to-Peer (P2P) Networking: An overlay technique on communication networks, which is implemented in the terminal equipment of users with Internet access. Since the millennium, many applications became popular on P2P networks starting with file sharing, voice over IP solutions.

Tunnel: Transmission through a tunnel establishes a point-to-point connection to carry data of one transmission protocol through a networks using different protocols and/or technologies. Virtual Private Network (VPN): Virtual private networks provide overlays on the network layer in order to connect separated networks at different locations via a telecommunication network. The IETF has developed a standard suite for VPNs on the Internet. The operator of a VPN can have limited visibility of the underlying network structure of a service provider supporting the VPN.

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Chapter LVI

Optimising P2P Networks by Adaptive Overlay Construction James Salter University of Surrey, UK Nick Antonopoulos University of Surrey, UK

Abstract Distributed Hash Tables (DHTs) have been used in Peer-to-Peer networks to provide query lookups in typically O(log n) messages whilst requiring maintenance of only small amounts of routing state. We propose ROME, a layer which runs on top of the Chord DHT to provide control over network size through monitoring of node workload and propose the use of processes to control the addition or removal of nodes from the network. We show that this technique can reduce further the hop counts in networks where available node capacity exceeds workload, without the need to modify any processes of the underlying Chord protocol.

Background With many media reports of increased piracy (Digital Spy, 2005) (one file-sharing server recently shut down indexed 170 million pirated files (MPA, 2006)), free-for-all access to illegal materials (BBC News, 2005) and promises of finding answers to previously incomputable problems emerging as a result of them (Anderson, 2002;Bohannon, 2005), Peer-to-Peer networks have become a hot topic not only of interest to

the scientific community, but to a wider audience too. Of course, not all coverage has been accurate, but P2P networks have nonetheless attracted much attention. As an emerging technology, there are many opportunities for research work that will provide real benefits for the future of Peer-to-Peer networks. In this chapter we look at the area of resource discovery. Since large collections of resources are distributed throughout such networks, searching and discovering the whereabouts of them becomes a vital function.

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Optimising P2P Networks by Adaptive Overlay Construction

Traditionally, networks were based on client/ to several others and have the potential to act as server architectures. Client workstations would both clients and servers. Resources are typically be connected to a central server which would hosted on nodes at the edge of the network, rather handle all requests. In this environment, resources than on dedicated servers. (for example files or databases) are held on the A pure P2P architecture is more robust than server, so client-to-client communication is rare a client/server architecture because the need for or non-existent. a central server, and thus the single point-of-failClient/server architectures allow for requests ure, is removed, although this comes at a cost. for resources to be resolved efficiently. Each Resources are spread throughout the network so client is directly connected to the server which it is no longer guaranteed that a requestor will means, as it is the central resource repository, a be directly connected to a provider, meaning it single hop over the network is all that is required may take several hops over the network to find to send a request. On the other hand, having a the required resource. central server leads to a single point-of-failure. In practice, it is rare for a network to have a Whilst communication is still possible if one of pure P2P architecture. Many are hybrids (Figure 1) or databases) are held on the server, so client-to-client the clientsresources fails, if(for theexample serverfiles is removed from positioned in-between pure P2P and client/server. communication is rare or non-existent. the network then none of the machines are able Not all nodes in hybrid P2P architectures have to be resolved efficiently. Each to access Client/server resources. architectures allow for requests for resources equal standing within the network like in pure P2P. client directly connected the server which means, as itnodes is the central resource repository, Largely dueis to success of theto World Wide Some take on additional responsibilities, a single hop over the network is all that is required to send a request. On the other hand, Web, we often view the Internet as a client/server becoming group managers or routers, which leads having a central server leads to a single point-of-failure. Whilst communication is still environment. Clients connect via Web browsers to morefrom organisation within the network. possible if one of the clients fails, if the server is removed the network then none of the Typically machines able tocontent access resources. to Web servers thatare return in response to they hold more information about the network requests. However, the original ARPANET was than a standard node, allowing for messages to Largely due to success of the World Wide Web, we often view the Internet as a client/server conceivedenvironment. to share computing resources be routed fewer Our discussion of P2P Clients connect via throughweb browsers to web serversin that returnhops. content in response out the United States. Machines were connected networks will treat them as high level networks to requests. However, the original ARPANET was conceived to share computing resources throughout the United States. Machines were connected as equal peers. As the Internet grew as equal peers. As the Internet grew it took on a running at the application layer. These networks it took on a client/server-like architecture. Recently though, the trend has begun to reverse as client/server-like architecture. Recently though, are overlaid on top of the lower level networking a new breed of peer-to-peer network has emerged (Minar, 2001). the trend has begun to reverse as a new breed layers, hence the term network overlay. of peer-to-peer network (P2P) has emerged (Minar, Pure peer-to-peer architectures tend toward the opposite of client/server architectures. 2001). There are no central servers. Instead, machines (often referred to as nodes) are directly connected to several others and have the potential to act as both clients and servers. Pure peer-to-peer (P2P) architectures tend Research Question Resources are typically hosted on nodes at the edge of the network, rather than on dedicated toward theservers. opposite of client/server architectures. There are no central servers. Instead, machines Previously, research into creating efficient reA puretoP2P architecture is more connected robust than a client/server because the forP2P a environ(often referred as nodes) are directly source architecture discovery schemes forneed use in

central server, and thus the single point-of-failure, is removed, although this comes at a cost. Resources are spread throughout the network so it is no longer guaranteed that a requestor will be directly connected to a provider, meaning it may take several hops over the network to the required resource. Figure 1. find Hybrid Peer-to-Peer Architecture

Figure 1: Hybrid Peer-to-Peer Architecture

In practice, it is rare for a network to have a pure P2P architecture. Many are hybrids (Figure 1) positioned in-between pure P2P and client/server. Not all nodes in hybrid P2P architectures have equal standing within the network like in pure P2P. Some nodes take on additional responsibilities, becoming group managers or routers, which leads to more

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Optimising P2P Networks by Adaptive Overlay Construction

ments has succeeded in developing models based on Distributed Hash Tables (DHTs) that distribute an index of resources across network nodes and are capable of resolving queries in typically O(log n) messages, where n is the number of nodes in the network (Zhao, 2003). Reducing the volume of messages required has concentrated on optimisations to the distribution of the index and the amount and type of routing information stored. However, since the number of messages is dependent on n, the number of nodes in the network, we believe that by creating a scheme to control how many nodes are members of the network, more efficient resource discovery can be provided. This leads us to our research question: Can we provide efficient, fault-tolerant resource discovery in peer-to-peer networks by controlling construction of the network overlay? Hosting the entire index on a single node would indeed allow for efficient discovery of resources (using O(1) messages) but has a single pointof-failure and, if the node is not well-chosen or the number of queries is very high, could cause the node to become overloaded. Simply saying that the network size should be minimal (i.e. a single node) is therefore an over-simplification, so consequently it is important to consider the fault-tolerance of the model in addition to its efficiency. Control of the number of nodes entering the network is not the only parameter that will affect the efficiency and fault-tolerance of the model. For example, a network constructed of a small number of low-quality nodes may not be any more efficient or fault tolerant than a larger network of higher quality nodes, because queries have a higher tendency to fail. Efficiency not only relies on a small number of messages required to resolve a query. We must take into account the number of messages required to maintain the network. For example, a model

884

would not be efficient if, although queries were resolved using few messages, messages were flooded across the network in order to update routing information every time a new node or resource was added. It may at first not seem important to further enhance the efficiency of resource discovery, especially considering existing approaches succeed in processing requests in a number of messages already logarithmic to the number of nodes in the network. For example, reducing the messages required to process a query from an average of twelve to nine in a network of ten million nodes seems trivial. However, when we consider the scale of P2P networks and that many users may be querying simultaneously, the seemingly small reduction appears more valid. If in the aforementioned example single queries originated on just a tenth of the network nodes, three million messages would have immediately been saved. Each message generated by the resource discovery model consumes bandwidth that could have been used to do the “real work” of the network, utilising the actual resources the query was seeking.

Introduction P2P network overlays can be broadly divided into structured and unstructured networks. Whereas in unstructured networks nodes may join the overlay at any point, more restrictions are placed on the positions nodes can take in structured networks. A major subclass within structured networks is Distributed Hash Tables (DHTs), based on the familiar hash table data structure, which provide guaranteed lookups and typically O(log n) hop counts whilst maintaining only small amounts of routing state (Kelaskar, 2002). In DHTs, each node is responsible for holding one or more hash table buckets, which together form the keyspace. Particular data values (e.g. a file) can be looked up by hashing their associated key (e.g. filename)

Optimising P2P Networks by Adaptive Overlay Construction

and searching the network for the node responsible for that part of the keyspace. One popular DHT is Chord (Stoica, 2003), which arranges nodes into a ring overlay structure. In addition to pointers to its predecessor and successor nodes, each node maintains a small finger table containing routing entries for a small number of other nodes in the network. Nodes are given identifiers and become responsible for a key if their ID most closely follows the numerical hash of the key. By following successor pointers and information in the routing tables, the node holding a value associated with a given key can be found within log2 n steps (½log2 n on average) where n is the number of nodes in the ring. Whilst these costs are low, messaging costs should be minimised in P2P networks to allow for the maximum possible bandwidth to remain available for the “real work” of the application running on top. In this chapter we present ROME (Reactive Overlay Monitoring and Expansion), an additional layer running above the standard Chord protocol allowing control over the construction of the network via the selection and placement of nodes within the Chord ring. ROME provides a monitoring process to detect under and overloaded nodes and add or remove nodes to service the workload. The size of a Chord ring has an impact on the number of hops it takes to resolve a lookup,

with smaller rings having better performance. Our primary motivation is to provide a mechanism for controlling the size of the Chord ring to ensure it is the minimum size possible, therefore optimising the number of messages consumed. As link speeds across the internet rise but users are increasingly charged for the bandwidth they consume, we believe number of messages to be a more important metric to optimise than latency which can vary dramatically over time.

System Model and Processes Figure 2 shows an example network running ROME on top of Chord. ROME runs on each machine in the network and consists of a set of processes (ellipses) and data structures (rectangles). Processes include a traffic analyser allowing us to monitor Chord-related network traffic without needing to modify the underlying Chord protocol, and actions to add, replace and remove nodes. ROME-related data structures store monitoring data, a copy of the node’s Chord data captured using the traffic analyser and ROME specific data such as the address of the bootstrap server, the node’s capacity and locking information to prevent multiple ROME actions being undertaken simultaneously on a single node.

Figure 2. ROME Architecture and Processes C urrent Z ero

N ew M achine

C hord ID = 25

B ootstrap S erver ID = 57

N ode R equests

U pper Lim it T hreshold

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ID = 48

T arget

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ID = 1

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ID = 46 N ode P ool

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A dd N ode

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Optimising P2P Networks by Adaptive Overlay Construction

Additionally, we show a bootstrap server because a new machine must know the address of an existing node that it can use to establish a connection with the network. New machines contact the bootstrap server, a well-known machine that lists the addresses of the nodes currently connected to the network. This is common in P2P networks but in ROME, rather than immediately supplying the new machine with the address of the existing network node and allowing it to join instantaneously, the addresses of machines that have requested to join the network are held on the bootstrap server (node pool). Instances of ROME running on nodes already in the ring send requests to the bootstrap server for the addresses of machines to add to the ring only as they are required. ROME ensures the underlying Chord ring is of near optimal size by monitoring the workload on each node using the traffic analyser and responding to node under or overload by adding, replacing or removing nodes. A target workload, plus lower and upper thresholds are defined for each

node. In real terms, this workload is a measure of memory (to store key and routing information) and processor time/cycles (for running the protocol processes). Depending on the implementation, these capacity values are either determined by the higher-level application or explicitly defined by the user of the machine. Action is taken when the current workload is either over the upper threshold or below the lower threshold, with the aim of restoring the workload as closely as possible to the target by adding, removing or replacing nodes. Figure 3 shows a simplified flowchart of the ROME process running on a node. We discuss the various actions taken in more detail to follow.

Node Locking Taking action has the potential to influence the workload of the node’s immediate successor in the ring, so both the node and its successor must be locked before actions can be taken, thereby removing the likelihood of chain reactions and

Figure 3. Simplified ROME Flowchart No

START

Register with Bootstrap Server

Pause, then send Heartbeat

Added to ring?

Yes Remove node, update pred/succ pointers

Yes

Successor accepts remove request?

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Calculate Chord ID, send to new node, send Chord insert messages Transfer Chord ID to new node, update pointers on pred/succ nodes

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Above Upper T

Optimising P2P Networks by Adaptive Overlay Construction

over-compensation. If action is required, ROME will send a message to the node’s successor. A message will be sent back in response, indicating whether or not the lock was successful. If the lock was unsuccessful, ROME will wait for a random exponentially increasing time period (as per the standard Exponential BackOff Algorithm) before restarting the monitoring process. Otherwise, ROME will lock the current node and attempt to resolve the under/overload by performing an action. Placing the current node in control of the locking procedure and only seeking to lock the successor prevents potential deadlock situations from occurring. Dependent on whether the node is under or overloaded, actions are attempted in a predefined order (detailed descriptions of each action are as follows): If a node is overloaded, ROME will send a message to the bootstrap server and attempt to replace the current node with a more capable one from the node pool. If no suitable node is available, the bootstrap server will send details of a node that can be added to the ring to take on the additional workload. If the overload has not been resolved, the process will be restarted following a wait defined by the Exponential BackOff Algorithm. If a node is underloaded, ROME will seek to remove the node (as long as doing so would not cause the node’s successor to become overloaded). If this is not successful, ROME will wait for a time period (defined again by the Exponential Back-Off Algorithm) and restart the monitoring process. Throughout ROME we exploit a property of Chord suggested in (Stoica, 2003), that Chord will store a node’s keys on r nodes following the node actually responsible for that key space, so that no information is lost if the node fails. Therefore, when we modify nodes in the Chord ring, keys are automatically migrated by the underlying Chord protocol. Although ROME could migrate the keys itself, the advantage of this approach means ROME does not need direct access to any Chord data structures.

Node Joins and Network Initialisation As would be the case for a standard Chord implementation using a server-based bootstrapping mechanism, a machine wishing to join the network contacts the bootstrap server. Our bootstrap server adds the address of the new machine in its node database, rather than providing the address of an existing network node. By preventing machines immediately joining the ring, we automatically filter out unreliable nodes that disconnect after a very short period. The traffic analyser running on the new machine will detect the join request message, triggering ROME to send the bootstrap server a message containing the capacity the machine is prepared to set aside for the network. On machines that have registered, ROME sends periodic heartbeat messages to the bootstrap server, which allows the server to evaluate and record the machine’s reliability (many missed heartbeat messages indicate an unreliable machine with low uptime). Prior to the initialisation of an instance of the network, a bootstrap server must be defined. (We assume here the bootstrap server is external to the network itself but in implementations a machine could of course run the relevant bootstrap server processes and also be eligible to become a network node). The bootstrap server starts with an empty node database. A machine wishing to join the network then contacts the bootstrap server. The ring is immediately created with this node, as per the standard Chord process. Since no keys will have been stored at this point, the node ID cannot be determined using the methods outlined as follows. Therefore, the initial node is given node ID 0. With the network initialised, the standard processes then continue as defined.

Ring Expansion At first glance, the obvious action to take to add capacity to the ring is to expand it by adding an additional node from the pool of available ma887

Optimising P2P Networks by Adaptive Overlay Construction

chines listed on the bootstrap server. However, it may be that there is an available machine with higher capacity that could cope with the current node’s full workload. Since one of our goals is to keep the ring as small as possible, a direct node replacement is preferable (if possible), with the addition of another node to share the current node’s workload as a second option. When ROME has identified that a node is overloaded, it sends a message to the bootstrap server requesting the address of a replacement machine with a target capacity greater than its current_workload. The bootstrap server searches its database of available machines and, providing there is a match, replies with a message containing the address of the matching machine with the highest reliability to ROME running on the current node and removes the machine from its database. The most reliable node is found by calculating the percentage of heartbeats received from it by the bootstrap server since its initial registration:

PercentageReceived =

HeartbeatsReceived CurrentTime - RegistrationTime ExpectedIntervalBetweenHeartbeats

The node ID of the old node is transferred to the new machine by ROME running on the old node. Messages are then sent by ROME on the old node to the Chord protocol layer running on the old node’s successor and predecessor nodes to alert them to update their references to the

node’s new IP address. Other nodes’ finger table information will be updated as the standard Chord stabilisation routine is run. The migration of keys is handled by the standard Chord protocol. If, on the other hand, the bootstrap server is unable to give the address of a machine matching the supplied capacity requirements, the second option of adding a new node to the ring to share the current node’s workload must be utilised. The bootstrap server searches for a machine with a target capacity of (current_workload - currentnode_target_capacity). Once the overloaded

node has received a message containing the address of a machine to be added to the ring, it must organise for its keys to be shared between the current node and the new node. This is achieved by inserting the new node into the ring between the current node and its predecessor, giving the new node a node ID such that Predecessor_ID < New_Node_ID < Current_Node_ID. The actual node ID is chosen based on the cumulative workload generated by each key on the current node and how much workload must be moved to the new node. Figure 4 shows how 300 units of workload could be moved to a new node from the current node by (in the example) transferring keys 164-186 to the new node. Similar to the aforementioned, a message informs the new node of its node ID. The new node is inserted into the ring by ROME on the current node sending insert

Figure 4. Example key transfer from current node to new node during node addition C urrent N ode ( ID :197) previously responsible for key space 164-197 ( total w orkload = 1000)

N e w n o d e (ID :1 8 6 ) re sponsib le fo r key space 1 6 4 -1 8 6 ( 3 0 % o f o ld w o rklo a d )

T otal w orkload = 3 00

C u rre n t n o d e (ID :1 9 7 ) now re sponsib le fo r key space 1 8 7 1 9 7 ( 7 0 % o f o ld w o rklo a d )

T otal w orklo a d = 7 00

w orklo ad 164

888

key

186

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Optimising P2P Networks by Adaptive Overlay Construction

messages to the standard Chord protocol running on itself, its successor and its old predecessor. Again, key migration is handled by the Chord protocol.

eration can take place. If the node can be removed, ROME sends a message to the Chord protocol on its predecessor informing it its successor is now the current node’s successor. Similarly, it sends a message to its successor informing it its predecessor is now the current node’s predecessor. Finally, ROME sends a message to the bootstrap server, which triggers the node to be re-added to the pool of available nodes.

Node Removal The actions introduced are mechanisms to cope with nodes becoming overloaded and to better organise workload within the ring. However, it is also possible that workload may decrease to an extent that the underload cannot be rectified through re-organisation, making it unnecessary to keep all nodes in the ring. When ROME wishes to remove its host node, it sends a remove request message to its successor containing its current workload. ROME on the successor checks whether the node’s workload combined with the successor’s current workload is over the successor’s upper threshold. It responds with a message indicating whether the remove op-

Evaluation To evaluate ROME we built a simulator in Perl. The simulator supports two Chord rings, one emulating a standard implementation of Chord and one emulating a Chord ring with ROME running on top. This allows a direct comparison of ROME with standard Chord and the benefits or increased costs to be explored. 1000 nodes were made available to each ring. The ROME-specific

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node thresholds were set as follows: A node was considered underloaded if its workload fell below 5% of its total capacity, with the upper threshold has been set at 95%. The target workload was set at 50% node capacity. 500 lookups were randomly generated and executed each clock tick. The experiment was repeated 3 times to ensure no anomalies were present. During the experiment the network workload was varied over time as indicated by the grey line superimposed on the graphs in Figure 5, up to the total capacity of all available nodes. This distribution was decided upon because it allows the experiment to show how the ROME-enabled network behaves under different workload conditions. One of the key functions of ROME is its management of the size of the underlying Chord ring. The potential message savings are directly derived from this. The number of nodes in the network running Chord (blue) and the network running ROME (red) at every clock tick throughout the experiment is shown in Figure 5a. As expected, the number of nodes in the Chord network remains constant throughout since no management of the volume of nodes is included in the standard Chord protocol. In contrast, using ROME the number of nodes varies with the change in network workload. The number of nodes in the ROME-managed ring never reaches 1000 because of the effects of node churn. Whereas nodes are immediately added to the Chord ring when they join, with a ROME-managed network these nodes are first added to the node pool. Therefore, with 10 simulated node failures and 10 node joins per clock tick, at most approximately 980 nodes will be present in the ROME ring with another 20 remaining in the node pool. In the ROME-enabled network, all nodes are added to the ring (with the exception as described previously) when the network-wide workload approaches 75% of the total capacity of all the available nodes. A small fluctuation in the number of nodes can be seen even when the workload is

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kept constant at the end of the experiment (from approximately clock tick 11500). This again is due to node churn: Failures cause some nodes to disappear from the ring and sometimes better nodes are available in the pool to provide replacements for these due to higher capacity nodes joining the network. This results in the workload of two or more failed nodes being supported by a single replacement. The opposite also applies, being that sometimes extra nodes must be added to the ring due to a single replacement node not being available. Figure 5b shows the percentage of queries that were successfully completed each clock tick in the Chord and ROME-enabled rings. The light blue and tan lines show the actual percentage recorded at each iteration, while the darker blue and red lines plot a 50 point moving average of the data. We define a successful query as a lookup successfully routed that can also be answered by the destination node (overloaded nodes are forced to drop queries they cannot handle, so even though a query reaches the destination it may not be successfully processed). Due to ROME’s management of node overload, the ROME-enabled ring exhibits a lower percentage of failed queries than Chord for the majority of the experiment, except where only a small number of nodes exist in the ring. However, since these failures occur when the ring is small and thus the number of messages taken to process them is also small (see Figure 4c), it could be argued that they could be re-run without incurring an exceptional cost. The major goal of ROME is to reduce the number messages required to process queries in Chord. As shown in Figure 5c, this is largely achieved although there are some minor fluctuations above Chord around time 4000 (when workload is 75%) and time 8500 (again, when workload is over 75%). It is reasonable to assume that network owners may wish to consider whether running ROME is appropriate if they expect their network’s workload to consistently approach ring capacity.

Optimising P2P Networks by Adaptive Overlay Construction

An average of 591.4 messages were saved using ROME each time tick based on the 500 queries submitted (with -190 the minimum and 2663 the maximum savings). In order for ROME-enabled rings to truly provide message savings over standard Chord rings, the lookup message savings as shown before must not be at the expense of increased maintenance message cost. Maintenance messages include those generated by the standard Chord join and stabilisation routines, plus ROME-specific messages used to transmit the necessary data and instructions for actions to be performed and heartbeat messages sent to the bootstrap server from nodes currently residing outside the ring. The maintenance costs of the ROME-enabled ring and the equivalent Chord ring are shown in Figure 5d. The total cost of ROME actions plus maintaining the underlying Chord ring is consistently less than the maintenance cost of standard Chord. The cost includes heartbeat messages (one every clock tick for every node in the bootstrap server’s node pool), meaning ROME’s minimum maintenance cost lies at approximately 1000 messages rather than at zero as might initially be expected. On average, 4423.4 messages were saved per time tick with a minimum saving of –35 messages and a maximum of 6746.

Conclusion and Future Work We have shown that, by adding a layer to control node joins and processes to monitor node workload, we are able to construct smaller than standard Chord rings with the benefit of smaller messaging costs throughout the network. Although we add more functionality to the bootstrap server, this is only utilised for node join, replacement and removal functions. As with a standard Chord implementation, the ring is still capable of performing its core functions if the server becomes unavailable. Through simulation we have proved that construction of small rings is desirable, and

demonstrated this is possible using ROME when the total capacity of machines available to become members of the ring exceeds the workload placed on the ring. The results gathered show that ROME can be best applied in situations where the sum of the capacities of all the nodes wishing to connect to the network is much greater than the workload being placed on the network. If these are near the same value, most or all the nodes must be added to the underlying Chord ring and therefore ROME provides little benefit. In some cases where the workload and capacity are near identical, the increased number of changes to the ring caused by ROME’s actions can lead to the message cost of lookups exceeding that of a standard Chord ring. Application developers should consider adoption of ROME in applications where workload is likely to be lower than the capacity offered by the connected nodes. An obvious example of this is a simple distributed lookup application: A user would need to be connected to the network to issue a lookup, thus there are likely to be many machines wishing to join the ring (although these can be hosted in the node pool rather than be members of the underlying Chord ring). The workload associated with each lookup is likely to be low so the total network-wide workload could be handled by a small number of machines. Utilising ROME for this application would enable lookups to be routed in fewer messages than in a standard Chord ring where each machine would have to be a member of the ring. A widely held assumption has been that nodes wishing to participate in a Peer-to-Peer network immediately join the network. Through this work we have shown that it is possible to reduce the message cost associated with a network by controlling the addition and removal of nodes to ensure the overlay contains only enough nodes to service the current workload. This has implications for the design of future Peer-to-Peer network overlays and protocols.

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ROME could be used as the foundation for building new classes of application such as realtime searching technologies to allow peers to share any type of resources or complex collaborative applications which take the notion of collaboration further than the existing fairly simplistic interactive whiteboard applications (MacDonald, 2003). Although ROME has been presented as an optimisation within Peer-to-Peer networks, it may also be applicable in other domains such as wireless or ad-hoc networks which have a similar property of dynamic machine joins and leaves as in P2P. Especially where networks are made up of low bandwidth connections, the number of hops between points in the network needs to be minimised. Maximising usage of devices within such environments would ensure the network (and the investment behind it) is fully utilised. ROME could also be linked in with a mechanism supporting High Throughput Computing on distributed computing resources. One such mechanism is Condor (Litzkow, 1998), which sends a user-submitted job for execution on a remote machine within a pool of available machines. This appears similar to the concept of the node pool on a Bootstrap Server. ROME operations could be developed to run on the remote machine with a possible view to utilising add, replace and remove actions to manage the job workload. The underlying Peer-to-Peer network protocol used within this work has been Chord. However, it is likely that the method of controlled construction of the network overlay can lead to message savings in other structured DHT-based Peer-to-Peer networks where the lookup cost is proportional to the number of nodes in the overlay. Calculations related to placement of new nodes to ensure they take on the correct proportion of workload will be more difficult in DHT-based overlays which rely on multi-dimensional keyspaces rather than the one-dimensional keyspace found in Chord, but this is merely a more complex problem to solve rather than something insurmountable.

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It may also be possible to expand the ideas presented in ROME to apply in the domain of unstructured P2P networks. However, there are many different issues to be addressed before this could be attempted. In unstructured networks there is no concept of keyspace and nodes dealing with workload or hosting files relating to their area of keyspace. Another form of organisation would need to be implemented or adapted to allow for workload to be moved around in these networks so that nodes could take on extra workload and under-utilised nodes could be removed from the overlay. Peer-to-Peer networks are in a collection of technologies that are shifting power towards users in what can be viewed as the democratisation of the Internet. They bring new challenges to stakeholders, whether they are ISPs, network administrators, developers or end users. However, they also bring new opportunities to produce applications not possible in the traditional client/server based Internet environment. In the future we may see P2P combined with emerging technologies such as wikis, podcasts, semantic Web, application service providers and others, allowing for evermore exciting advances. However, all these applications will rely on the underlying network overlay at the application layer. The work in this chapter presents a possible extension to this base service, allowing more efficient lookups to take place in structured DHT-based networks. Other topologies will doubtless be developed in the future, but the idea of controlled construction of the network overlay leading to reduced messaging costs where these are proportional to network size will remain.

Related Work Many extensions and modifications to the standard Chord protocol have been proposed, several of which share our aim of reducing the number of hops required to process a lookup. However, to

Optimising P2P Networks by Adaptive Overlay Construction

our knowledge none of these do this by controlling the expansion of the Chord ring itself. In fact, ROME is complementary to these extensions. Using them together may provide even greater message savings. Kaashoek and Karger (2003) combine Chord with de Bruijn graphs to produce Koorde, allowing for varying amounts of routing information to be stored and thus achieving hop counts between O(log n) and O((log n)/log log n), where n is the number of nodes in the network. It is clear that a reduction in n would also reduce Koorde hop counts. The authors also suggest that finding a system that is load balanced and degree optimal (optimising the amount of routing information stored) is an open question. With our control over node joins, small ring size and placement of nodes, we believe ROME can go at least some way to achieving this. Single hop lookups are achieved by storing a global routing table on every node by Leong and Li (2004), but only in circumstances where network churn is low, something rarely achievable in realistic P2P implementations. Other researchers have explored creating hierarchies of multiple Chord rings. Garcés-Erice et al (2003) demonstrate reduction in hop counts through their assumption that high quality nodes are always available to add to the top layer of their hierarchy. Mislove and Druschel (2004) build sub-rings within administrative domains, exploiting node locality to reduce latency of lookups. Locality could also be exploited using our protocol in the single layer rings, becoming an extra selection criteria when searching the node pool for machines to join the ring. Ratnasamy et al (2002) reviewed several DHTbased routing algorithms and direct researchers toward several open questions. They suggest that node heterogeneity is extreme, which is a property we use to our advantage. By allowing only the best nodes to join the ring, we build a ring with less probability of failure than one including all available nodes.

References Anderson, D. P., Cobb, J., Korpela, E., Lebofsky, M., & Werthimer, D. (2002). SETI@home: An Experiment in Public-Resource Computing. Communications of the ACM, 45(11), 56-61. BBC News. (2005). Legal fight hits music pirates. British Broadcasting Corporation. Retrieved November 14, 2005, from http://news.bbc.co.uk/1/ hi/entertainment/music/4438324.stm Bohannon, J. (2005). Grassroots Supercomputing. Science, 308(5723), 810-813. Digital Spy. (2005). Report: Illegal file sharing on increase. Digital Spy Limited. Retrieved November 16, 2005, from http://www.digitalspy. co.uk/article/ds26272.html Garcés-Erice, L., Biersack, E. W., Ross, K. W., Felber, P. A., & Urvoy-Keller, G. (2003). Hierarchical peer-to-peer systems. Parallel Processing Letters, 13(4), 643-657. Kaashoek, M. F., & Karger, D. R. (2003). Koorde: A simple degree-optimal distributed hash table. In Proceedings of the 2nd International Workshop on Peer-to-Peer Systems (IPTPS03). Berkeley, CA. Kelaskar, M., Matossian, V., Mehra, P., Paul, D., & Parashar, M. (2002). A study of discovery mechanisms for peer-to-peer applications. In Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid Workshop on Global and Peer-to-Peer on Large Scale Distributed Systems (pp. 444-445). Berlin, Germany. Leong, B., & Li, J. (2004). Achieving one-hop DHT lookup and strong stabilisation by passing tokens. In Proceedings of the 12th International Conference on Networks (ICON2004). Singapore. Litzkow, M., Livny, M., & Mutka, M. (1998). Condor – A Hunter of Idle Workstations. In Proceedings of the 8th International Conference

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of Distributed Computing Systems (ICDCS 1998) (pp. 104-111). San Jose, CA, USA. MacDonald, M. (2003). Peer-to-Peer with VB .NET. New York: Springer-Verlag. Minar, N., & Hedlund, M. (2001). A Network of Peers: Peer-to-Peer Models Through the History of the Internet. In A. Oram (Ed.), Peer-to-Peer: Harnessing the Benefits of a Disruptive Technology (pp. 3-20) Sebastopol, CA, USA. O’Reilly. Mislove, A., & Druschel, P. (2004). Providing administrative control and autonomy in structured peer-to-peer overlays. In Proceedings of the 3rd International Workshop on Peer-to-Peer Systems (IPTPS04). San Diego, CA. Motion Picture Association. Belgian & Swiss Authorities Break Razorback2 [press release]. MPA, 21 February 2006. Ratnasamy, S., Shenker, S., & Stoica, I. (2002). Routing algorithms for DHTs: some open questions. In Proceedings of the 1st International Workshop on Peer-to-Peer Systems (IPTPS02). Cambridge, MA. Stoica, I., Morris, R., Liben-Nowell, D., Karger, D. R., Kaashoek, M. F., Dabek, F., & Balakrishnan, H. (2003). Chord: a scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking, 11(1), 17-32. Zhao, B., Huang, L., Stribling, J., Rhea, S., Joseph, A., & Kubiatowizc, J. (2003). Tapestry: A resilient global scale overlay for service deployment. IEEE Journal on Selected Areas in Communications, 22(1), 41-53.

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Key Terms Distributed Hash Table: A method for storing hash tables in geographically distributed locations in order to provide a failsafe lookup mechanism for distributed computing. Fault Tolerance: The ability of a system to respond gracefully to an unexpected hardware or software failure. Hash Table: A lookup table that is designed to efficiently store non-contiguous keys that may have wide gaps in their alphabetic and numeric sequences. Network Overlay: An overlay network is a computer network which is built on top of another network. Nodes in the overlay can be thought of as being connected by virtual or logical links, each of which corresponds to a path, perhaps through many physical links, in the underlying network. Network Traffic: Data transmitted over the network at a given moment. P2P: A distributed network architecture may be called a Peer-to-Peer network, if the participants share a part of their own hardware resources (processing power, storage capacity, network link capacity, printers). They are accessible by other peers directly, without passing intermediary entities. The participants of such a network are thus resource providers as well as resource requestors (Servent-concept). Query Hops: The number of times the query has been forwarded.

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Chapter LVII

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier Susan J. Chinburg Rogers State University, USA George Scheets Oklahoma State University, USA

Abstract The network carrier must utilize the full potential of existing physical infrastructure before any new investments can be considered. Much work has been done to develop optimal design methodologies that generate a “best” design but designs often have to be changed to meet operational considerations, potentially mitigating any optimization benefits. This work proposes to expand the optimal network design process by applying a process borrowed from Finance and Operations Research/Management Science literature known as the Efficient Frontier or production frontier analysis. Using this idea, a portfolio of designs differing in cost, and number, size and location of nodes will be developed and from that the efficient frontier will be defined. By comparing any subsequent design to the frontier, the network designer can have an understanding of the impact of changes in the design strategy to the long-term cost effectiveness.

I. Introduction Mitigating the risk of expanding a network in today’s economic climate requires that the network carrier utilize the full potential of existing infrastructure before any new investments are

considered. The design of actual networks is the product of multidimensional constructs of performance and reliability optimized around a certain factor or factors such as cost or reliability. Typically, a methodology is created to define near optimal solution depending upon the constraint

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Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

parameters to be considered. Much work has been done to develop optimal design methodologies using one or multiple objectives but these problems are intractable and NP-hard and can require complex computational solutions that are often best approximations (Yun et al, 2001). Even after the optimal design has been developed, during implementation the design often has to be changed to meet operational considerations, potentially mitigating any optimization benefits. Design of telecommunications networks is a complex, usually iterative, process with several objective functions such as low cost, reliability, security, and survivability. To find the optimized design, an exhaustive analysis must examine every possible combination of all parameters thereby proving the best fit to meet the specified design characteristics. Finding near-optimal solutions requires fast heuristic algorithms, establishing acceptable constraints or bounds and then “relaxing” these constraints so the solutions can be found with reasonable resources and time (Kennington et al 2007). The bulk of published research and literature in mathematical modeling and optimization deals with ways of making this very complex problem simpler and easier to solve. Mathematical modeling and optimization are well-developed and mature areas of research with a variety of articles available for the interested reader who is referred to Bertsekas (1998), Sanso and Soriano (1999), Grover and Doucette (2001), and Kennington et al (2007) for broader overviews. This paper is intended to discuss the impact of applying the efficient frontier concept to network design of a new service overlay and assumes that a method for defining the optimal network design has been adopted. The method used to calculate the optimal design and cost of the case studies in this chapter will be presented, but that method is not the main focus of this effort. Applying the concept of the efficient frontier is the main focus of this chapter. Using the efficient frontier or production frontier, a concept borrowed from finance, agriculture

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economics, and operations research literature, a design process can be established that creates not just a single optimal solutions but also a set of solutions, (Markowitz, 1959 and Farrell, 1957). A brief discussion of the Efficient Frontier concept will be presented but interested readers are referred to Fare et al (1994) and Copeland et al. (2005) for mosolutions for the problem. By developing a set of optimal solutions using design heuristics that best fit the given project, an envelope of cost functions is created. The lower boundary of this envelope is the efficient frontier or suite of “best” designs as far as the parameters used for the optimization. The efficiency of any design is the relationship of the final cost of a design to the frontier. Evaluating the distance any point is from the efficient frontier gives a measure of how efficient the design is as related to the parameters used in the optimization. If the cost of a design lies upon the frontier it is considered efficient, the further off the frontier, the less efficient the design. By understanding the impact of design changes to the final cost of the network, well-informed design changes can be implemented with regard to final or long-term cost. Complicating the design process for communication networks is that there are often multiple objectives such as reliability, security, and recoverability in addition to low cost. For multiple-objective optimization problems a set of Pareto-optimal solutions can usually be defined (Sawaragi et al 1985 and Koopmans 1951). The set of Pareto solutions becomes the efficient frontier for the design process. Pareto optimal solutions do not necessarily optimize all objective functions but create a set of candidate solutions that can be individually evaluated for use. The input parameters to these problems are usually arrived at through analysis related to the subject area being investigated (Yun et al 2001). The method presented by Yun et al (2001) involves extensive mathematical multiple objective optimization utilizing much computational resources. This paper presents a similar process in that an efficient

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

frontier is created using a set of optimal single objective optimization solutions developed from sensitivity analyses.

II. Study Methodology In this section an outline of a set of experiments conducted with a mixed integer linear programming (LP) problem formulation of the service overlay with growth problem (SOGP) is presented. The SOGP was formulated to solve the problem; Overlay System Cost = Overlay Switch Cost + Overlay Link Cost, and provides a general formula useful for examining the installation of a new network overlaid on top of an already existing network. This problem is expressed by the following equation. Overlay System Cost n = ∑ [xi (C1 + K1 * (nodei_traffic) α)] [switch chassis costs] i=1 n + K 2 ∑ xi (nodei_traffic)β i=1 [traffic or connections costs] n n + K L * ∑ ∑ (trafficij)χ * (distanceij)δ i=1 j=1 [link costs] 1 = indicates which node from the set N = {1, i 2,…,n} where n is the total number of nodes in the overlay design. i,j∈ N = {1, … n}. xi = binary constant, (0 or 1) indicating whether or not an overlay switch is located at node i. C1 = initial cost of chassis K1 = arbitrary unit cost of a chassis nodei_traffic = the amount of traffic flow that will move through the node i. Also called the number of connections needed at a switch. K 2 = an arbitrary unit cost assigned to each connection.

K L = an arbitrary unit cost factor. trafficij = link capacity from node i to node j. Distanceij = route miles from node i to node j. α = Exponential factor that modifies the impact of traffic flow upon the size of the switch chassis. α < 1. β = an exponential factor that will describe the shape of the curve, β < 1. χ and δ; exponential factor for traffic and distance respectively. For this study χ and δ = 1 but other cost models could have these values less than one. For instance, some Frame Relay service providers do not price connectivity in terms of distance, so δ could be equal to zero. Other cost models with χ < 1 could show economies of scale related to capacity. The closer α is to 1, the closer the function is to linear. Various nodal distribution strategies for an overlay were examined by manually controlling the node input to the design for the four case study legacy networks. The basic assumption in this investigation was that an underlying legacy network topology (nodes and connections between nodes) exists and a new service overlay was to be built on top of the existing network structure with no additional physical links or nodes added. New service traffic flows were transmitted over the existing topology. SOGP, modeled after Grover and Doucette 2001 and Chang and Gavish 1993, creates a sum of shortest paths for the traffic flow solution for the input design criteria of nodes, links and traffic flow values. Definitions: • • • •

n is the number of nodes, N is the set of such nodes. N = {1, 2, 3, … , n} i,j ∈N. A is the set of possible bi-directional edges in the graph on the set of nodes N. T is the set of time periods, t, in the study. T = {1, 2, … , t}. Dt is the set of all non-zero flow demand quantities exchanged between nodes, in-

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•

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dexed by r. D will be different for each time period t. The elements of Dt represent the traffic to be carried by the network for each city pair. drt is the amount of flow demand associated with the rth demand pair in D for period, t. O[r] is the node that is the origin for the rth flow demand pair in D. TR[r] is the corresponding target or destination. clij (= clji) is the incremental cost of adding one unit of capacity to edge (i,j). These incremental steps can be the same or different for each time period. wrtij is the amount of working flow of the rth demand routed between nodes (i,j) on link i,j or j,i for period t. lwijt is the working capacity assigned to the edge between nodes (i,j) to support all working flows routed over that edge for period t. Sjt is the fixed cost of a switch at node j. Sjkt is the fixed cost of a switch at node j for size increment k. There are incremental steps, k, in this function determined by the number of ports needed to carry all the traffic flow coming through and into the switch at node j. These incremental steps can be the same or different for each time period. The value of Sjk at each increment of k will be arbitrarily defined. cpj is the incremental cost of adding one unit of capacity to switch at node j. These incremental costs can be the same or different for each time period. Pjt = the number of connections needed in switch at node j to accommodate all the traffic flow that will enter or leave this switch. It is the sum of the demand flow routed to/from and through node j. CSjk is the incremental cost of the switch chassis. CSjk is a constant value set before the model is analyzed. These incremental

•

•

•

•

•

costs can be the same or different for each time period. This formulation has them the same for each node. K is the set of incremental costs, k corresponding to the number of different sizes of chassis used in the model, b.. K = {0, 1, 2, …, k}. CNjk is the maximum number of connections that any switch size will allow. For each k there will be a predefined constant such as 1000, depending on the size of the switch chassis. M is an arbitrarily large constant that is greater than any capacity needed to accommodate all the flow through a switch. zjk is a binary variable (0,1) used to facilitate the step cost function of the switch chassis. The number of different sizes of the chassis, b, is the number of different values for the subscript k. K ={0,1,2, …, k). zjk will be 1 for the appropriate size of Pj and zero for the rest. Only one chassis will be installed at each node. When k = 0 there are no (0) connections for that nodes and therefore no switch at that nodes. xj is a binary variable (0,1) used to control the nodes that are allowed to have a switch in the design. This variable can be manually controlled.

Objective Statement: (see Box 1.) The objective statement 2 seeks to minimize the cost of the network overlay based on three factors, the cost of the node/switch chassis, the cost of each connection to the switch chassis and the cost of additional capacity on a link to support the required flow. Equations 3, 4, and 5 are standard flow balance constraints that require that all the flow leaves the source, all the flow arrives at the destination and that at all transshipment nodes the flow is balanced so that all the flow that enters the nodes leaves the node. Equation 6, the link capacity constraint, sums all work-

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

Box 1. Minimize

{ S xj Sjt

S t∈T

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+ S xj {cpjt * Pjt } + S {clijt *lwijt}} j∈N

2

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3

j∈ A

S wrtij - S wrtji = - drt for all r ∈ D, i = TR[r] and for all t∈T. 4 ∈Aj

∈A

S wrtij

- S wrtji = 0 for all r ∈ D, for all i ∉ {O [r] or TR[r] } and for all t∈T. j∈ A 5

∈A

lwijt = S wrtij + S wrtji for all i,j∈ A and for all t ∈ T. i,j∈ A

6

j,i∈ A

Pjt = lwijt + lwjit for all i,j∈ A and for all t ∈ T.

7

Pjt = 0.

14

ing flow, wrtij, and wrtji, that traverse this link to determine the amount of capacity needed on the link. Equation 7 is the switch size constraint that sums all working flows that go though this link to determine the number of connections needed for the switch at node j. Equation 8 says that the value of Pjt will be either zero if there is not a switch at this location or it will be less than M, that is a number sufficiently larger than any connection capacity needed at any switch. Equation 9 defines the binary choice variable, zjkt, defined for each node, j, as to which size of switch chassis

is installed at the node. Equation 10 determines the correct size of switch to be placed at a node based on the number of connections required to deliver the traffic flow. Equation 11 calculates the cost of the switch based on the previous constraint. Since this is a minimization problem the cheapest size will be selected based on the correct value of zjk from constraint 9. Equation 12 requires that there be only one switch size for each node if any at all. Equation 13 requires that the input to the next period, t, be the output of the previous period. And equation 14 states that the

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Three case studies then were conducted using a generic North American network based on that of WilTel (Figure 2), the NSFNet from the US research network, the beginnings of the Internet (Figure 3), and a generic Pan-European model based on that used in Maesschalck et. al., 2003 (Figure 4). The North American network has 27 nodes and 43 links. The Pan-European network has 28 nodes and 43 links. The NSFNet network model has 15 nodes and 22 links. The traffic matrix was developed using the population-based function as described by Cahn (1998). Population data from the US Census database was used for the North American and the NSFNet case studies. For the Pan-European topology the populations of the metropolitan city

Figure 1. Initial 9 node proof of concept model

working flow, wrtij, and wrtji, will be either zero or a positive number.

II.2 Case Study Topologies The initial legacy topology for proof of concept testing was a 9-node model (Figure 1).

Figure 2. The North American legacy topology based on the WilTel North American network. The number by each city name is an index Seattle 1 Albany 27 Minneapolis 15

Chicago 16 Cleveland 17

Salt Lake City 4 Denver

Boston 26

NYC 25

Cincinnati 18

Kansas City 14

San Francisco

DC 24

St Louis 13 Los Vegas 5

Los Angeles

Nashville 19

Charlotte 23

Tulsa 12 Atlanta 20

Phoenix 6

Dallas 10 El Paso 7 San Antonio 9

New Orleans Houston 11 Miami 22

Figure 3 The NSFNet legacy topology. The number by each city is an index Seattle 1 Ithaca 14 Boston 15

Ann Arbor 10

Princeton 13 Salt Lake 4 Pittsburgh 12 DC 11

Boulder San Francisco 2

Urbana –Champ 8

Lincoln 6

Atlanta 9

San Diego 3 Houston 7

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Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

Figure 4. Pan-European legacy topology. The number by each city is an index Oslo 27 Stockholm 28 Glasgow 2 Copenhagen 26

Warsaw 24

Dublin 1 Amsterdam 4

London 3

Hamburg 13

Berlin 25 Prague 23

Frankfurt 14

Brussels 5

Budapest 21

Strasburg 12 Paris 6 Munich 15 Bordeaux 7

Vienna 22

Zurich 11 Zagreb 18 Lyon 10

Belgrade 20 Milan 16

Barcelona 9 Rome17 Madrid 8 Athens 19

areas were from data supplied by European city mayors (http://www.citymayors.com/features/ euro_cities.html). Distance between each city pair was calculated using the Microsoft VirtualGlobe, 1998 edition. Three cost functions were used in this study, the cost of capacity on a link, the cost of the switch chassis and the cost of each flow connection in and out of the switch chassis. Cost models for the overlay were developed using generic cost functions based on previously published data from WilTel and other publicly available information. These functions were built from the network carrier perspective, essentially, the cost required to implement the new service overlay. Each unit of connection in the switch is a constant cost which in this study was arbitrarily set to 125. The actual switch chassis costs are a step function that is not generally linear and were set to $1000, $2000, $4000, $10000, and $20000 with switch sizes set to 1000 ports, 2000 ports, 4000 ports, 12000 ports, and 24000 ports respectively. Each unit of link cost is a function of the distance of the

link and the link capacity times a dollar amount. The distance was determined by summing the linear distances between the nodes traversed by the overlay link. For this study to keep link costs simple, the dollar amount was arbitrarily set to $1 per distance unit. Capacity multiplied by distance and by the unit link cost created the total link cost for each link. The SOGP formulation was implemented in single sequential periods with the topology output, including number, location and size of switches, the links and the capacity of links of one growth period as the input for the next growth period. The only difference between each period was the increase in the amount of traffic. Each node in the legacy topology would contribute traffic to the design, in the SOGP implementation; chassis and ports were allowed at all nodes including all the access-only nodes. These access-only node costs, chassis and ports, were manually deducted from the final costs to determine the final total cost for the overlay design.

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Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

The number and distribution of switches in the nodal distribution pattern in the service overlay were manually varied using different design strategies developed around both number of switches, node population size and location of the nodes in the backbone. To approximate network growth a five level traffic matrix was developed. 1X growth stage represented the traffic matrix calculated as described in Step 2 of this section. Four additional growth stages were calculated by multiplying the initial amount of traffic demand, 1X growth stage, by 1.5, 3.5 and 10 creating five growth stages 1X, 1.5X, 3X, 5X, and 10X. For this study each design strategy was modeled using all five-growth stages. The location of the backbone design for each scenario was established using the shortest path connections between each backbone node. Variations in design strategies were based on well-accepted design heuristics that would be common implemented, including number of overlay switches, edge versus central locations and population of the selected node (Cahn 1998). To control the population variable three groups of nodes were established based on population size of the city at the node, small, medium, and large, for each real world case study. III. Results of Case Studies Four separate case studies were evaluated, first, a small proof-of-concept 9-node legacy network (Figure 1) and then three larger closerto-real-world legacy models, a North American, NA, model (Figure 2), the NSFNet (Figure 3), and a Pan-European, PE, model (Figure 4). This section presents the results of the experimental analyses. The primary network carrier nodal backbone design strategy used to develop test network configurations used the philosophy that once a legacy node was in the overlay backbone the overlay switch handled all traffic flows passing through this node. Hereafter this will be referred to as design strategy 1. A secondary strategy 2 created a mesh topology with logical links between each node pair in the overlay backbone. The only

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traffic flow handled by an overlay switch in the full logical link mesh is traffic flow that originates and terminates at that switch location. Those nodes not in the overlay backbone will have access to the nearest overlay backbone switch and that switch will handle (originate and terminate) their traffic flow. Thru traffic flow passing through a node with an overlay switch will be processed by the assets of the underlying legacy network in design strategy 2. A limited number of mixed topologies, using a combination of legacy and logical links, were also evaluated.

III.2 The 9-node Case Study The 9-node network topology (Figure 1) is well connected with an average degree of connectivity of 4.4. Link distances for this model are an arbitrary value of 1 or 2 with an average of 1.4 and the switch costs are an arbitrary 10, 20, 30, 40 and 50 for sizes of 50, 100, 200, and 500 connections respectively. The unit cost constants of switch costs, KS, are much greater than link costs, K L, KS >> K L. The most cost effective overlay design evaluated for this model is the one switch centralized in a star pattern (Figure 5). An intermediate distribution of nearly 45% (4 out of 9) of the legacy

Table 1. Network characteristics of case study legacy networks. Network characteristics of number of nodes, connectivity of nodes, population of nodes, number of links, link length are presented in this table. C is the connectivity of the nodes in the network Network

9 node

Nodes

C

Pop

Links

Link length

#

Average

Ave in M

#

(Mean)

9

4.44

NA

20

1.40

PE

28

3.04

1.42

43

248.21

NA

27

2.93

3.79

43

436.95

NSFNet

15

3.19

3.92

22

1085.45

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

Figure 5. Experimental total cost results for the 9-node legacy network. One switch on a central location was the lowest cost solution evaluated by this study while one node switch located at a periphery location was more costly 2500

Full logical link Mesh

10X 5X 3X

2000

1.5X 1X

cost

1500

Full logical link Mesh 1000

Full logical link Mesh 500

0 0

1

2

3

4

5

6

7

8

9

10

9-Node model Legacy Nodes in Overlay

Fi gure 5 Experimental total cost results for the 9-node legacy network. One switch on a central location was the lowest cost solution evaluated by this study while one node switch located at a periphery location was nodes in the service much greater than the unit costs of links, KS more costly. overlay is the next most cost

>> effective long-term approach evaluated. K L. Link distances were minimal and therefore hadwith limited impact upon the were total cost. For this For theFor 9-node legacy topology, overlay designs the 9-node legacy topology, overlay designs switches at all nodes evaluated using both design strategies. There were switches at all nodes with logical type of overlay network design where total switch with switches at all nodes were evaluated using links between all nodes, design strategy 2, and the other design used the links of costs are dominant, total network the costs tend to both design strategies. There were switches at all locationfirst will by have minimized costs designallstrategy 1. The centralized be impacted switch costs.link Once switch nodes withlegacy logicaltopology, links between nodes, design because all traffic flow paths are available so the sum of carried traffic will be minimal. Each costs are minimized then link costs need to be strategy 2, and the other design used the links design will have the same number of overlay switch chassis but the number of centralized node location with of the legacy topology, 1. The Theaddressed. connections perdesign switch strategy will be different. design withAlogical links (design strategy 2) one centralized location will have minimized link switch that has high connectivity is the lowest will have the minimal number of connections because the overlay switches will handle cost costs because traffic flow paths overlay design evaluated for thiswill legacy network only all local traffic flows andare noavailable pass through traffic flow, so the switch chassis be of so the sum carriedsize traffic will be (Figure 5). Asthe the overlay design strategy includes theofsmallest possible. Forminimal. this 9-node legacy network backbone design strategy creating a full logicaloflink mesh becomes the lower costlegacy designnodes, evaluated. Theswitch Each design will have the same number overlay switches at more the total cost function for this legacy network is dominated by the cost of switches including both cost switch chassis but the number of connections per cost increases and therefore the total design chassis and portThe costs, as well the unit costincreases. of switches being muchfrontier greaterfor than the switch will be different. design withaslogical The efficient this legacy tounit costs of links, KS >> KL. Link distances were minimal and therefore had limited links (design strategy 2) will have the minimal pology connects the low cost one-switch scenario, impact upon the total cost. For this type of overlay network design where total switch number of connections because the overlay for this first study the lowest design; to costs are dominant, total network costs tend towhich be impacted byisswitch costs.cost Once switches will handle only local traffic flows and the intermediate distribution design and switch costs are minimized then link costs need to be addressed. A centralized node then to no pass through traffic so the switch the full logical link design. location with flow, one switch that haschassis high connectivity is mesh the lowest cost overlay design will be ofevaluated the smallest sizelegacy possible. For this 9- 5). As the overlay design strategy includes for this network (Figure switches at the more legacy nodes, the total switch costNorth increases and therefore theNSFNet total node legacy network overlay backbone design III.3 American and design cost increases. The efficient frontier for this legacy topology connects the low strategy creating a full logical link mesh becomes Case Studies cost one-switch scenario, which for this study is the lowest cost design; to the the lower cost design evaluated. The cost funcintermediate distribution design and then to the full mesh logical link design. tion for this legacy network is dominated by the The North American, NA, and the NSFNet models cost of switches including both chassis and port have network characteristics of longer link discosts, as well as the unit cost of switches being Page 10 903

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

tances, average of 437 miles and 1085 respectively overlay networks. A full mesh overlay that uses (Table 1). For the implementation of these network the shortest path connections between each node designs the unit cost of link capacity was set to pair has the smallest possible total link capacity 1, K L = 1. While the unit cost of switches, KS, is requirement of all possible network designs [Cahn, III.3 North American andKNSFNet Case Studies , long much greater than the unit cost of links, 1998]. With this cost structure, traffic flow paths L link distances result in the dominant factor being need to be minimal for link costs to be minimized. North NA, and the NA NSFNet models network characteristics of longer the cost of The links. The American, total link costs for the In thesehave experiments, all logical links on a full link distances, average of 437 miles and 1085 respectively (Table 1). For the overlay designs evaluated range from $30 Million mesh overlay network are routed over the shortest implementation of these network designs the unit cost of link capacity was set to 1, KL = to less than1.$80 Million while total switch costs legacy network path. While the unit cost of switches, KS, is much greater than the unit cost of links, KL, were in thelong range of $5 Million to less than $30 For the NA designs evaluated in link this study, link distances result in the dominant factor being the cost of links. The total Million. For the NSFNet case study the link cost the designs with overlay switches at most or all costs for the NA overlay designs evaluated range from $30 Million to less than $80 Million $10 while were in the range $5 Million less than Million. range was between andtotal $40switch Millioncosts and switch nodesoftend to be thetolower cost.$30 The key to this NSFNet the linkThe cost range wasmay between $10the andlong $40 link Million and and the cost range For wasthe between $1case and study $6 Million. trend be both lengths switch cost range between $1 and $6 Million. The key to of minimizing these NA key to minimizing costs forwas these case studies low connectivity the nodescosts of theforlegacy case studies was to focus on minimizing link costs. was to focus on minimizing link costs. and NSFNet designs. The low nodal connectivity For both these network case studies, the fully does not allow many path choices thus total path For both these network case studies, the fully distributed switch approach with a full distributedlogical switchlink approach with a full logical lengths overlay designs maystrategy be similar. mesh overlay and a switch at every nodebetween following backbone design link mesh 2overlay and cost a switch at every node The dominant costs thiscost model due to the is the most effective overlay design evaluated (Figurelink 6 and 7).inThe structure following backbone design strategy 2 is the most longer link lengths must be minimized for total used in these experiments, coupled with the long link distances, tilts the low cost advantage highly connected networks. A full mesh overlay uses thecost cost effective overlay towards design evaluated (Figure 6overlaycost to be minimized. While the that lowest total path connections between each nodedesigns pair hasevaluated the smallest possible and 7). Theshortest cost structure used in these experifor this studytotal for link both the NA capacity all possible networkcase designs [Cahn, 1998]. Withwere this the costlowest link ments, coupled withrequirement the long linkofdistances, tilts study and the NSFNet structure, traffic flow paths need to be minimal for link costs to be minimized. In these the low cost advantage towards highly connected cost they were not the lowest switch cost indicating experiments, all logical links on a full mesh overlay network are routed over the shortest legacy network path. Figure 6. North American Legacy Overlay Design studies. All of the five growth stages are presented but the efficient frontier is drawn only for the 10X growth period. Lowest cost design strategies evaluated for this study are the distributed overlays with switches at all or most nodes 90000000 1X Growth stage 1.5X Growth Stage

80000000

3X Growth Stage 5X Growth Stage

70000000

10X Growth Stage

60000000

cost

50000000

40000000

30000000

20000000

10000000

0 1

6

11

16

North American Legacy Nodes in Overlay

904

Page 11

21

26

full mesh

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

Figure 7. NSFNet Overlay Design studies. All ofAllthe fivefivegrowth stages presented but the Figure Legacy 6 North American Legacy Overlay Design studies. of the growth stages are are presented but the efficient frontier is drawn only for the 10X growth period. Lowest cost design strategies evaluated for efficient frontier is drawn only for the 10X growth period. Lowest cost design strategies evaluated are this study are the distributed overlays with switches at all or most nodes. the distributed overlays with switches at all or most nodes 40000000 1x 1.5x

35000000

3x 5x

30000000

10x

cost

25000000

20000000

15000000

10000000

5000000

0 0

2

4

6

8

10

12

14 16 logical link mesh

legacy nodes in overlay

Figure 7 NSFNet Legacy Overlay Design studies. All of the five growth stages are presented but the efficient frontier is drawn only for the 10X growth period. Lowest cost design strategies evaluated are the distributed overlays with switches at all or most nodes.

unit cost of link capacity was set to 1, K L = 1. that link costs drove total cost with this legacy wasorthe same as unitwith costoverlay for switches, NA designs in this study, theThe designs switchesK atS,most topology and For the the factors used inevaluated this study. all nodes tend to be the lower cost. The key to this trend may be both the long link defined for the NA and the NSFNet models, so The efficient frontiers, suites of best designs lengths and the low connectivity of the nodes of the legacy NA and NSFNet designs. K >> K L. For the designs evaluated in this case evaluated in this study, forconnectivity the designs arenotapThe low nodal does allow manyS path choices thus total path lengths thelink range of in switch costsdue wastofrom $3 to 15 proximately linear decreasing frommay onebeswitch between overlay designs similar. The study, dominant costs this model the longer link lengths be minimized total costwhile to be minimized. While the range for linkthe costs was $10-30 to switches fully distributed at allmust nodes in the for Million lowest total cost designs evaluated for this study for both the NA case study and the Million. The differences between switch and link legacy network for the NA and NSFNet case studNSFNet were the lowest link cost they were not the lowest switch cost indicating that costs of the designs evaluated in this study are ies (Figure 6 link andcosts 7). As previously mentioned, drove total cost with this legacy topology and the factors used in this study. much less thanstudy, the other larger in the NA and studies costs TheNSFNet efficient case frontiers, suiteslink of best designs evaluated in this for thetwo designs arecase studies approximately linear decreasing from fully distributed at allare nodes andtoinswitches some instances actually very similar. tend to dominate the cost function. For the NAone switch in the legacy network for the NA and NSFNet case studies (Figure 6 and 7). As Among the designs evaluated for this research, and NSFNet topologies increases in switch costs previously mentioned, in the NA and NSFNet case studies link costs tend to dominate the the full logical mesh overlay was again the lowest are offset by cost decreases in For linkthecosts. Increased function. NA and NSFNet topologies increases in switch costs are offset by (Figure 8). link costs in more centralized one-switch overlay decreases in link costs. Increased link costs incost moredesign centralized one-switch overlay designs are due to increased of backhaul The of traffic flows. These increased linkwas the next one-switch overlay approach designs are due to increased amounts of amounts backhaul costs offset the decrease in switch costs with fewer overlay switches. most cost effective design evaluated in this study of traffic flows. These increased link costs offset but the location of the overlay switch was critical the decrease in switch costs with fewer overlay (Figure 8). A central location of high connectivity switches. was important in lowering the total cost of the overlay. There are several possible reasons for this. III.4 Pan-European Model Case Study Page First, 12 the location of the switch at a centralized node in the legacy network is important because Key topology characteristics of the Pan-European, link distances tend to be minimized which in turn PE, network are shorter link distances than NA or minimizes backhaul costs. Periphery locations for NSFNet and more nodes with high connectivity a switch require longer flow paths thus increasing (Table 1). For the PE model network designs, the

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III.4 Pan-European Model Case Study

Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

Key topology characteristics of the Pan-European, PE, network are shorter link distances than NA or NSFNet and more nodes with high connectivity (Table 1). For the PE model network designs, the unit cost of link capacity was set to 1, KL = 1. The unit cost for switches, KS, was the same as defined for the NA and the NSFNet models, so KS >> KL. the designs evaluated this case overlay study, thedesign range of switch costs from $3 to 15growth periods Figure 8. For Pan-European LegacyinNetwork studies. Five was traffic demand Million while the range for link costs was $10-30 Million. The differences between for each design scenario were efficient frontier onlythan on the theother 10X data. The solid switch and link costs of modeled. the designsThe evaluated in this study is aredrawn much less line indicates the efficient frontier for the designs with full logical link mesh overlays, design strategy two larger case studies and in some instances actually are very similar. Among the designs evaluated for this research, full logical mesh again the 2. For design strategy 1 that utilized thethe direct links of theoverlay legacywas topology thelowest efficient frontier is a cost design (Figure 8). dashed line 35000000 1X growth stage 1.5X growth stage 30000000

3X growth stage 5X growth stage 10X growth

25000000

cost

20000000

15000000 Design strategy 1 Design srategy 2

10000000

5000000

0 1

6

11

16

21

26

PanEuropan Legacy Nodes in overlay

the distance traffic flow must be backhauled. The efficient frontier for this Figure 8 Pan-European Legacy Network overlay design studies. The Five traffic demand growth periods forcase study when design scenario The location efficient frontier isdrawn drawn only the 10Xthe data.full Thelogical solid linelink mesh shows degree of each connectivity forwere themodeled. periphery to on include indicates the efficient frontier for the designs with full logical link mesh overlays, design strategy 2. For also has an effect upon the total cost, the higher the lower cost designs have more design strategy 1 that utilized the direct links of the legacy topology the efficient frontier isto a dashed line. switches disthe connectivity of the switch location, the lower tributed over the full PE legacy network (Figure 8). The of one-switch overlay approach was the next most cost effective designstrategy evaluated in all switches on the total cost the overlay. When using design 1 with this study but the location of the overlay switch was critical (Figure 8). A central For the lower cost one-switch overlay designs the backbone handling all traffic moving through location of high connectivity was important in lowering the total cost of the overlay. evaluatedThere in this volume the First, the thelocation node toof draw the efficient arestudy, severaltraffic possible reasonsfrom for this. the switch at a frontier, the opposite node location was not aninimportant inisinseen. Centralized centralized node the legacy factor network importantrelationship because link is distances tend to be switch designs in turn minimizes backhaul costs.tend Periphery locations a switch fluencing minimized total cost.which The lowest cost one-switch to be less costlyfor when using design strategy overlay design had the switch located at node 14 1 for the PE legacy network evaluated. Were the (Frankfurt, see Figure 8). This location ranked 21 design strategy 2 applied to overlay backbones Page 13 out of 28 in population size but was a centralized consisting of a smaller number of overlay switches, node location with a degree of connectivity of 5. designs with costs lower than that of the single Periphery locations of similar connectivity to that node designs, but in most cases higher than that of node 14 but with higher traffic flow demands of the full mesh, are to be expected. The network showed a somewhat higher total cost. This implies designer using the design heuristics, knowledge that the volume of traffic flow from any given of the traffic flow matrix, and other undefined node, while important to the total overall cost, model constraints could develop a set of designs at least for designs evaluated, was less important that define a more continuous efficient frontier than minimizing backhaul distances. for the problem.

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Designing a New Service Overlay on a Carrier Network Using the Efficient Frontier

IV. Summary Defining the lowest cost overlay for a legacy network will depend upon the relative value of link cost to switch cost, the traffic flow demands, and the connectivity of the network. When switch costs dominate, minimizing switch costs is the first key to keeping the total cost down. For other topologies where link costs dominate the number of switches becomes less of a factor in the total cost function than minimizing link costs. Determining the dominant influence in the cost function will be the key to minimizing costs and predicting the shape of the efficient frontier. Efficient frontiers for each case study, based on the designs evaluated, were drawn indicating that for the NA and NSFNet case studies the distributed approach with switches at more nodes tend to be more cost efficient, regardless of whether design strategy 1 or 2 is used. For the PE topology case study, based on the designs evaluated for this study, the two design strategies produce different results. Using design strategy 2 with a full logical link mesh design switches at every legacy node was the lowest cost design. If that design philosophy is not used, then a single switch that is located at a central highly connected node is the more cost effective. Defining Efficient Frontiers for suites of network designs is one methodology to understand the impact of cost changes. Future research will focus on other methods of grouping data to define the “best” solution.

V. References Bertsekas, D. (1998). Network Optimization Continuous and Discrete Models. Athena Scientific, Belmont, MA. Cahn, R. S. (1998). Wide-Area Network Design: concepts and tools for optimization. Morgan Kaufman Publishers, San Francisco, CA.

Chang, S. G., & Gavish, B. (1993). Telecommunications network topological design and capacity expansion: formulations and algorithms. Telecommunications Systems, 1, 99-131. Copeland, T. E., Weston, J. F., & Shastri, K. (2005). Financial Theory and Corporate Policy. Pearson Addison Wesley, Boston, MA. Drezner, Z., & Hamacher, H. W. (2002). Facility Location: Application and Theory. Springer-Verlag, Heidelberg, Germany. European city mayors population database. Retrieved May 15, 2005. (http://www.citymayors. com/features/euro_cities.html). Fare, R., Grosskopf, S., & Knox Lovell, C. A. (1994). Production Frontiers. Cambridge University Press, Cambridge, Great Britain. Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society, 120, 253-281. Grover, W. D., & Doucette, J. (2001). Topological Design of Survivable Mesh-Based Transport Networks. Annals of Operations Research, 106, 79-125. Kennington, J. L., Olinick, E. V., & Spiride, G. (2007). Basic mathematical programming models for capacity allocation in mesh-based survivable networks. Omega, 35, 629-644. Koopmans, T. C. (1951). Analysis of production as an efficient combination of activities, in ed. Koopmans. Analysis of Production and Allocation (33-97). New York, NY: Wiley. Maesschalck, S., Colle, D., Lievens, I., Picavet, M., & Demeester, P. (2003). Pan-European Optical transport networks: An availability-based comparison. Photonic Network Communications, 5, 203-225. Markowitz, H. M. (1959). Portfolio Selection: Efficient Diversification of Investment. New Haven, CN: Yale University Press.

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Sanso, B., & Soriano, P. (1999). Telecommunications Network Planning. Kluwer Academic Publishing. Sawaragi, Y., Nakayama, H., & Tanino, T. (1985) Theory of Multipleobjective Optimization. New York, NY: Academic Press Yun, Y. B., Nakayama, H., Tanion, T., & Arakawa, M. (2001). Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis. European Journal of Operational Research, 129, 586-595.

VI. Key Terms Carrier Network: A communications service provider network. Efficient Frontier: The frontier represents the lower boundary of a suite of optimal designs. The efficiency of any design is the relationship of the

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final cost of a design to the frontier. Evaluating the distance any other design outcome is from the efficient frontier gives a measure of how efficient the design is as related to the parameters used in the optimization. The process was first defined for investment portfolio management and later expanded to production management operations. Network Design: An iterative process in which planning, development, topology and realization of a new communications service that meets needs from the perspective of service users and or network operators. The design of actual networks is the product of multidimensional constructs of performance and reliability optimized around a certain factor or factors such as cost or reliability New Service Overlay: An overlay of new service upon an existing communications network.

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Chapter LVIII

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS Mohamed Zaki Azhar University, Egypt Salah Ramadan Azhar University, Egypt

Abstract The cellular principle is an effective way to guarantee efficient utilization of the offered radio band. Although PCS networks use the cellular principle, the next generation of PCS networks needs more improvements in location management to face the increased number of users. Both an Enhanced ProfileBased Strategy (EPBS) for small-scale roaming and a Caching Two-Level Forwarding Pointer (C2LFP) strategy for large-scale roaming have been proposed. This chapter introduces a model that unites the above two strategies. The idea behind this model is based on applying those two location management strategies and specifying the physical parameters of PCS networks from mobility management’s point of view so that the underlying solutions can be more cost effective for location management. An evolutionary method using a constraint Genetic Algorithm (GA) has been used to achieve network parameters optimization. For convenience, we selected the planning problem with an appropriate set of parameters to be treated both genetically and analytically. Thus one can easily verify accuracy and efficiency of the evolutionary solution that would be obtained from the genetic algorithm. For more realistic environments, GA could be used reliably to solve sophisticated problems that combine the small-scale and large-scale roaming parameters of PCS networks. A case study is presented to provide a deep explanation of the proposed integration approach.

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

1 Introduction The limited bandwidth for Personal Communication Systems (PCS’s) can restrain the growth of the population of mobile customers. In addition, the next-generation of PCS networks should meet the increased requirements in both bandwidth and performance to offer the new demanded services. The bottleneck here is the number of location registrations which leads to a higher demand for switching capacity and signaling links. Definitely, the mobile users must be able to move from one location to another while maintaining access capacity to services regardless of their locations. Therefore, the role of location management in the network is to keep track of Mobile Terminals’ (MT’s) location information so that calls can be correctly delivered (Lin, 2003; Lin,2000). Location management is the process of allowing the network to know the attachment point of the mobile user for a successful call delivery. Current location management techniques involve certain database architecture and signaling messages transmission over the PCS network (Tabbane, 1997; Wong, 2000). The location management process in a PCS network may use a two-tier system of Home Location Register (HLR) and Visitor Location Register (VLR) databases (Akyildiz, 1999). According to these databases, the Figure 1. PCS Network Architecture

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existing location management scheme allow the mobile user to perform location update at HLR level whenever that user crosses the boundary of an VLR area and deregisters at the previous VLR. Thus, the registrations will generate high signaling traffic as a result of many location updates to the HLR. Since many users are far away from their HLRs, heavy signaling traffic over the network can occur. This problem has been solved in the caching two-level forwarding pointer scheme. In the case of roaming inside the VLR area, every time the user crosses the boundary of a location area, the existing location management scheme allows the mobile user to perform location update at the VLR level. Thus, the VLR location updates result in high traffic when many users update their locations to the VLR. This problem has been solved in the enhanced profile-based scheme; Figure 1 shows PCS network architecture illustrating two types of roaming. We developed those two roaming solutions where one is for small-scale roaming (Ramadan S. M., 2004) and the other is for large-scale roaming (Ramadan S. M., 2003). However, the PCS planner can face a problem in developing the locator program using such both solutions in one framework. Moreover, an evolutionary approach is used to construct this framework, by making use of a GA chromosome, to integrate the small-scale and

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

large-scale roaming parameters of PCS networks. Since the combined model involves a constrained optimization problem, the parametric constraints (such as power, setup delay, and list size) are discussed in details. For the reason that the next generation will provide high bandwidth access, there are no bandwidth constraints. The model results are then presented and mapped to physical model network equipments and dimensions are determined. This chapter is based heavily on (Ramadan S. M., 2003, Ramadan S. M., 2004, Ramadan S. M., 2007-A, and Ramadan S. M., 2007-B). It is organized as follows: • •

• • •

Background for both of EPBS and C2LFP schemes that will be combined. Discussion of the need of integrating those two proposals and description of the significant parameters for the proposed combining model. The combination process details. The optimization problem. A case study for our network design with discussion for the results and mapping the physical network parameters.

2 Background Location management is one of the most important issues in PCS networks. As the number of mobile users increases, location management

scheme under the IS-41 (EIA/TIA, 1991) or GSM MAP (ETSI, 1998) faces many problems such as increasing traffic in network, and bottleneck occurrence to the HLR. To overcome the entire network problems, two solutions have been proposed: one for small-scale roaming and the other for large-scale roaming.

2.1 Caching Two-Level Forwarding Pointer Scheme: This scheme is based on exploiting the cache entry stored in a local switch. This switch maintains the recent location of a mobile user when he moves from a Mobile Switching Center (MSC) area, which is served by MSC/VLR, to another MSC/VLR. Whenever the mobile user is accessed through certain switch, an entry contains a mapping from the ID of the mobile user to that of its serving VLR is added to the cache. When a call is initiated for a mobile-user at nearest switch, this calling switch first checks the existence of a cache entry for the mobile user. On one hand, if no entry for the mobile user exists, then the call delivery operation for two-level forwarding pointer scheme is invoked to locate the mobile user; on the other hand: if the mobile user is still residing under the same VLR, a hit occurs and the mobile user is found, and if the mobile has already moved to another location which is not associated with the same VLR, a miss occurs and the call delivery operation, such as two-level forwarding pointer scheme, is invoked to locate

Figure 2. Call delivery model Incoming call at a certain switch Path 1 Cache entry is absent from the switch Two-level forwarding pointers scheme is used to locate the mobile user

P ath 2 Cache entry is maintained in the switch Cache hit occurs

Cache miss occurs

Two-level forwarding pointers are used to locate a user without querying HLR

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Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

the mobile user without querying the HLR. Figure 2 describes the call delivery model for C2LFP scheme. The two-level forwarding pointer C2LFP strategy is accurately described in (Ramadan S. M., 2003).

2.2 Enhanced Profile-Based Scheme This strategy develops a profile-based scheme (PBS) that is considered a location area (LA)-based strategy; LA is a piece of VLR region. The LAs, that the Mobile Terminal (MT) is most likely to be present in, are registered in a data structure called User Information Table (UIT). The UIT is manipulated to create the main list that is registered to the network during a location update (one copy in the MT and another copy in the network database). If the behavior of a mobile user is changed, then the profile should be modified. Procedures manipulating the UIT will modify the main list after reaching predefined interval. The modified UIT is sent through certain registration message from the MT to the system. However, the system overwrites the profile using the modified version. Each record in the main list contains three fields, the first two fields are same as in the PBS scheme: the first is for the LA ID, and the second deals with the probability of a user being in this location area ai, and the last field defines the User State US which specifies the likelihood of this LA to be present in, the state field has one of two values {1 or 2}; by this additional field, a virtual list is created contains the LAs that are the MT is more likely to be present and marked with state 2. This virtual list, called favorite sub-list, stores the LAs that the MT is more expected to be present in his/her daily routine as the work and home LAs. The US value is only sent to the network to notify if the MT follows the LAs that belong generally to the main list or especially to the favorite sub-list. The proposed strategy does not need to send a copy of the modified profile in each registration message, but it can send

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after agreed interval. The advantage of EPBS strategy is to allow the number of LAs stored in the main list to be increased, thus reduces the cost of location update. Furthermore, the existing of multiple states of the MT reduces the cost of paging. The total cost of location update and paging procedures is obviously decreased in the MTs that have relatively constant mobility pattern. The cost computation of the EPBS strategy will be used later. In EPBS strategy, we assume that all of location areas in the list are under the same MSC/VLR; and if the MT moves to a new LA within another MSC, then the system follows the location management method for large-scale roaming (C2LFP scheme). The EPBS strategy algorithm is divided into location update and paging procedures. The algorithms of location update and paging are illustrated in (Ramadan S. M., 2004).

3 The need of combination The question here is how those two solutions can run simultaneously, and what would be their combined results. By integrating these solutions in one framework, the network planner may get one coherent model that can answer the aforementioned questions and can find out the physical dimensions of the PCS network. Also, the proposed model possesses optimization features to help in determining a cost-effective location management scheme. In what follows, our model parameters and constraints are illustrated.

3.1 Network Dimensions Parameters This group includes only static parameters depending on the fluid model to demonstrate the network dimensions parameters (Thomas R., 1988). The fluid model characterizes comprehensive movement behavior like the flow of a fluid. Mobile users are assumed to move at an average velocity of v, and their direction of movement

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

is uniformly distributed over [0,π]. Assuming that the mobile users are uniformly populated with a densityρ, the location area boundary is of length L, and the number of crossings through LA per unit time U is used in our modeling and is given by: ρ vL U= π

RLi =

(1)

Assume the number of zone groups is n, the number of crossings Ui for zone group i (where i = 0, 1, 2, …., n) depends on the velocity vi and density ρi of mobile users in this zone, and the perimeter Li of an LA in this zone where Li =2πRi. The perimeters Li or the radii Ri are the network dimensions parameters. Then Ui is obtained from

Ui =

ρi vi Li = 2 ρi vi Ri π

The MSC area is actually emerged into four zone groups where each zone group has certain mobile user velocity and density parameters. The weight λi of each zone group i is obtained from Ui

∑U i i =1



(4)

Where Numi represents the number of mobile users in zone group i, thus from (2)

RLi =

4vi 2vi = Li π Ri

(5)

The total cost of location management for mobile users follow the small-scale roaming (non-traveling users) will be discussed later in this chapter.

3.3 Large-Scale Roaming Parameters

3.2 Small-Scale Roaming Parameters

4

Ui Numi

(2)

The small-scale roaming depends on the dimensions parameters because those parameters dynamically influence the rate of location updates for mobile users. It is important to note that the network dimensions parameters Ri should be determined carefully to design the physical model.

λi =

Where Ui represents the number of crossings of each zone group i. In fact, the rate of location update per user RL , for each zone group i, depends on the network dimensions parameters and can be obtained from

(3)

The high mobility users (traveling users) category can be classified by mobility traces which record actual movement behavior for certain segments of the population. In (Tang D., 2000), a seven-week trace has been analyzed the Metricom metropolitan-area packet radio wireless network. The results indicate that the locations, which mobile users frequently visit, are close to each other. In addition, the users’ movement pattern is Gaussian distributed around the radius of the network. The Stanford University mobile activity traces (Cox D., 1998) is a publicly available trace generator which includes simulation data of the Bay Area location information traces for voice calls. The large-scale roaming study has two types of parameters: static and dynamic. Some of static parameters depend on the traveling user mobility, and then the value of those parameters is determined by the results of tracing. These parameters are illustrated as follows:

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Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

•

pi is the call to mobility ratio for each user group i σi is the ratio between the cost of FIND operation in case of cache-hit and the cost of basic FIND operation for each user group i ρi is the probability that the cache entry is absent for each user group i qi is the probability that the cache-hit occurs for each user group i Ki is the ratio between the cost of level-1 and level-2 forwarding pointers for each user group i Ni is the number of incoming calls per time unit for each user group i which are determined using small-scale roaming study.

•

• • •

•

Other static parameters are independent such as •

•

• •

S2 The cost of setting up a forwarding pointer (level_2 pointer) between VLRs during caching TwoLevelFwdMOVE. T2 The cost of traversing a forwarding pointer (level_2 pointer) between VLRs during caching TwoLevelFwdFIND m The cost of basic MOVE operation F The cost of basic FIND operation

3.4 Physical Constraints The physical constraints play an important role in determining the suitable values of the system parameters. These constraints are considered the barriers that prevent the system parameters from taking invalid values. Hence, three constraints, excluding the bandwidth, are suggested. In fact, the bandwidth constraint has not been taken into consideration since the spectral efficiency of a wireless network is measured by bits/second per Hertz per cell (BHC), and such efficiency can be improved through frequency reuse and higher-

914

order modulation (Boleskei H., 2001) which are beyond the scope of this chapter.

3.4.1 Power Constraint According to radio wave propagation theorem the strength of the waves decreases as the distance between the transmitter and receiver increases (Rappaport, 2002), propagation model has usually focused on predicting the average received signal strength. This model, that predicts the mean signal strength for an arbitrary transmitterreceiver separation distance, is helpful to estimate the ratio coverage area of a transmitter; moreover, it characterizes signal strength over large separation distances (several hundreds or thousands of meters). Also, the free space propagation model predicts received power decays as a function of the separation distance (called the radius of LA in our model). Assume a receiver antenna is separated from a base station by a distance R. Then, the free space power received is given by (6).

Pr ( R ) =

2 PG t t Gr λ (4π ) 2 R 2 S

(6)

where Pt is the transmitted power, Pr(R) is the received power, Gt is the base station antenna gain, Gr is the receiver antenna gain, S is the system loss factor not related to propagation (S ≥ 1), and λ is the wavelength in meters. The received power Pr(R) at any distance R > R0 may be predicted from (6), or may be measured in the radio environment by taking the average received power at many points located at a close-in radial distance R0 from the transmitter. The reference distance must be chosen so that it lies in the far-field region, and R0 is chosen to be smaller than any practical distance used in the mobile communication system. From (6), the received power in free space at a distance greater than R0 is given by

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

2

R  Pr (R ) = Pr (R0 )  0   R

(7)

Then

R = R0

Pr (R0 ) Pr (R )

(8)

If the received power decreases the radius of LA increases. The received power should not decrease under the level it can not be detected. If the threshold of the received power is PTH, then the radius of LA i is constrained by

Ri ≤ R0

P0 PTH

(9)

Each zone in MSC area for small-scale roaming has a different close-in distance R0, and the radius of LA in each zone Ri is constrained according to (9).

3.4.2 List Size Constraint This constraint controls the number of LA registered in the list and the number of LAs in a virtual list (favorite sub-list). In (Ramadan S. M., 2004), the relation between the cost of small-scale location management and the number of LAs was

discussed. The study showed that the list size can be increased up to certain threshold point since after this point the cost of location management is not acceptable. Consequently, the list size must be considered in optimizing the cost of location management in the PCS network.

3.4.3 Setup Delay Constraint This constraint controls the length of forwarding pointer chain from Mobile Agent/VLR to another agent and the length of forwarding pointer chain from VLR to VLR (Ramadan S. M., 2003). For high mobility users, the longer the chain length is the more reduction in the total cost of largescale roaming, but the more setup delay. Thus the total chain length must be chosen large enough to accept the setup delay.

4 The Combination An evolutionary model is proposed to integrate, the network dimensions, small-scale roaming and large-distance mobility management. Because of numerous interactions between the system parameters and constraints, a genetic-based algorithm is used with the advantage of clarity and robustness. Figure 3 shows the proposed model and illustrates its parameters. An initial chromosome structure is passed to the genetic algorithm module, and then after

Figure 3. Combined model diagram Chromosome Structure Large-Scale Roaming From N1 to N7 Small-Scale Roaming From R1 to R4 Network Dimensions

K1 K2

K1,opt GA Module

Y Z R1

K2,opt Y,opt

System Constraints

Z,opt

Mapping

Optimal System Parameters

R1,opt

R2

R2,opt

R3

R3,opt

R4

R4,opt

915

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

running the module under certain constraints, the optimal chromosome containing the optimal system parameters is generated. The results of combining scheme rely upon a global combinatorial optimization process, where all the system parameters are combined in one frame represented by the chromosome.

iv. If the nth population consists of allowed candidates then so does the (n+1)th What makes it difficult to define an applicable GA for a COP is clearly item (iv). This difficulty is mitigated by correctly maintaining the problem constraints in the underlying representation, operators and fitness.

4.1 Process Nature 4.2 The EPBS calculations The basic idea is to use genetic operators that take constraints into account. An operator can take constraints into account in two ways (Eiben A. E., 1995; Kielmann T., May 1999). i. ii.

It ensures that some of the prescribed constraints always hold It directs the search by applying heuristics in such a way that the rest of the constraints will be satisfied.

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About the Contributors

Angeliki Z. Agorogianni was born in Larisa, Greece on May 8, 1973. She received the Dipl. degree in electrical engineering from the Aristotle University of Thessaloniki, Greece and the Master in Business Administration from the University of Macedonia, Greece in 1996 and 2001 respectively. Since 1997 she has been working in the Telecommunications Center of the Aristotle University of Thessaloniki, Greece. Her research interests include distance-learning technologies, data modeling, service oriented architectures and enterprise architecture planning. Cajetan M. Akujuobi received the BS degree from Southern University, Baton Rouge, LA, in 1980, theMS degree from Tuskegee University, AL, in 1983, and the PhD degree from George Mason University, Fairfax,VA, in 1995, all in electrical engineering, and the MBA degree from Hampton University, Hampton, VA, in 1987. He is a professor in the Department of Electrical Engineering and is the founding director of Analog and Mixed Signal, DSP Solutions and High Speed (Broadband) Communication Programs at Prairie View A & M University, Prairie View, TX. He is also the founding director of the Center of Excellence for Communication System Technology Research. His research interests include signal/image processing and communication systems (broadband telecommunications) using such tools as wavelet and fractal transforms; compressed sensing/compressive sensing. His other research interests are in the areas of digital signal processor solutions, analog mixed-signal systems, and control system-based communications. He was a Participant and collaborative Member of ANSI TIE1.4 Working Group that had the technical responsibility of developing T1.413, Issue 2 ADSL standard. He has published extensively and has also written many technical reports. He was selected as one of the U.S. representatives for engineering’s educational and consultation mission to Asia in 1989. Prof. Akujuobi is a Senior Member of ISA, ASEE, SPIE, and Sigma Xi, the Scientific Research Society. He is one of the founding corporate members of the IEEE Standards Association (IEEE-SA), Industry Advisory Committee (IAC). Nana K. Ampah is currently a post-graduate student at Prairie View A & M University and also an Electrical Engineer with Jacobs Engineering, Houston, Texas. He is a student member of IEEE and belongs to organizations such as Ghana Institute of Engineers - GhIE (Associate Member) and Ghana Institute of Management and Public Administration (GIMPA) Alumni Association (Member). Nana K. Ampah graduated from Prairie View A & M University with anMSE.E. in Communications in May, 2004. He also graduated from Kiev Polytechnic Institute (KPI) in Kiev, Ukraine in June, 1993 with anMSE.E. specializing in Power Systems and Networks. He was also awarded a Post-graduate Certificate in Urban Management by GIMPA in June, 2001. He worked with the Electricity Company

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About the Contributors

of Ghana for 8 years and has over 6 years experience in the design, construction, commissioning and management of urban and rural electrification projects. He was a project engineer under a World Bank funded urban/rural electrification project from 1996 to 2002. He also worked with Skanska Jensen International as a Materials Coordinator (Consultant) on a World Bank funded rural electrification project in 1997. He is currently doing research work in the communications network security area involving the development of Intrusion Detection and Prevention Systems (IDS/IPS) for Homeland Security and Enterprise Networks. Georgios N. Angelou was educated at Democritus University of Thrace, Greece and received the Diploma degree in Electrical Engineering, in 1995. He also received a MSc in communications & radio Engineering from King’s College London in 1997 and a MSc in techno-economics from the National Technical University of Athens in 2002. He worked in telecommunication industry, in companies Siemens and Nokia, for four years as a technical consultant. He is a PhD candidate in information systems at the University of Macedonia, Thessaloniki. His current research interests are ICT business analysis and technology investments evaluation. Nick Antonopoulos, Dr. Nick Antonopoulos is currently a senior lecturer (US Associate Professor) at the Department of Computing, University of Surrey, UK. He holds a BSc in physics (1st class) from the University of Athens in1993, an MSc in information technology from Aston University in 1994 and a PhD in computer science from the University of Surrey in 2000. He has over 9 years of academic experience during which he has designed and has been managing advanced Master’s Programmes in computer science at the University of Surrey. He has published over 60 research articles in distributed systems, peer-to-peer networks and software agents. Luigi Atzori ([email protected]) is assistant professor at the University of Cagliari (Italy) since 2000. His main research topics of interest are in multimedia networking: error recovery and concealment, IP Telephony, video streaming, network QoS management. He has published more than 60 journal articles and refereed conference papers. Dr. Atzori has been awarded a Fulbright Scholarship (11/2003-05/2004) to work on video at the University of Arizona. He is editor for the ACM/Springer Wireless Networks Journal and is involved in the organization of several International Conferences on Multimedia Networking. Raquel Barco received her MSc degree in telecommunication engineering in 1997 and her PhD in 2007 from the University of Málaga (Spain). From 1998 to 2000 she worked at the European Space Agency in Darmstadt (Germany). From 2000 to 2003 she worked part-time for Nokia Networks. Since the end of 1999 she has been with the Communication Engineering Department, University of Málaga. Her research interests include satellite and mobile communications, mainly focused on self-management of radio access networks. Georges Baume, Dr. Georges Baume is a senior lecturer in the school of business at the University of Adelaide. He lectures in strategic management, corporate strategy, and corporate transformation, and is the strategy discipline leader for the school. Dr. Baume’s research interests include the development, implementation, and execution of internationalisation strategies and processes for service sector firms.



About the Contributors

He holds a PhD and an MBA from the University of Adelaide, and an M.Sc from Oxford University. He has won numerous teaching excellence awards for his work in MBA and executive education programs in Australia, Asia, and Europe. Lokesh B. Bhajantri received M.Tech degree in Computer Science and Engineering from Visvesvaraya Technological University (VTU), Belgaum, Karnataka, India, in 2005. He is presently working as a lecturer in the Department of Information Science and Engineering, Basaveshwar Engineering College, Bagalkot, Karnataka, India. His areas of interest include m-commerce, e-commerce, networking protocols, applications of mobile agents and real time systems. He has published few papers in national/international conferences. David Bell holds a BS degree in electrical engineering from Walla Walla College and aMS degree in Business Administration with an emphasis in Management Information Systems from California State University, Sacramento. He is currently pursuing a PhD in applied management and decision sciences with an emphasis in Information Systems Management from Walden University. For the past 18 years he has been teaching a wide variety of information systems courses at Pacific Union College, a private college in California’s Napa Valley. He enjoys exploring new technologies, photography, singing, and scuba diving. Fabrizio Boi ([email protected]) received his Dr. Eng. Degree in electronic engineering from the University of Cagliari, Italy, in 2006. In 2006 he started his PhD research activities with the Department of Engineering (DIEE) at the University of Cagliari. In 2007 he taked part of IKNOS research project as collaborator of DIEE which partners were Tiscali Italia SpA, CNIT and DIEE. In 2007 he joined in Open Media Center Lab of Sardegna DistrICT as collaborator at Sardegna Ricerche, Italy. His research interests are related to IP Telephony playout buffering, speech quality estimation (QoS on IP networks), NGNs performance management, home entertainment, home automation and multi-touch sensing devices. Mohamed Boucadair was an R&D engineer with France Telecom R&D in charge of dynamic provisioning, QoS, multicast, and intra/interdomain traffic engineering, and now works on VoIP services. He graduated from the Ecole Nationale Supérieure d’Ingénieur de Caen (Institut des Sciences de la Matière et des Rayonnements), a French school of engineers. Susan J. Chinburg received a BS Science Teaching and Mathematics from Minnesota State University, Mankato, MN in 1972, aMS in geology from San Jose State University, San Jose, CA in 1985 and a PhD in business administration in MIS and telecommunications in 2006. Currently she is an assistant professor at Rogers State University, Claremore, OK. Her research interests include telecommunications network analysis and design, applied applications of MIS techniques to other areas and information assurance and security applications and teaching in the online environment. She has worked for Conoco, Inc in exploration, development, research and systems analysis and for WilTel, (formerly Williams Communications Group) in optical network architecture. Chin Wei Chong is currently a lecturer in Multimedia University, Malaysia. She received her PhD in the area of knowledge management. She has published several papers in international refereed journals,



About the Contributors

conference proceedings and book chapters. Her research interests include knowledge management, human resource management, strategic management and multimedia learning system. Siong Choy Chong received his PhD from Multimedia University. He has published extensively in international refereed journals, conference proceedings and book chapters in addition to serving on a number of journal editorial boards. His research interests include knowledge management, human resource management, information technology management and entrepreneurship. He is currently the chief executive officer of Putra International College, Malaysia. Nicoletta Corrocher, Laurea in economics (Bocconi University, Milan), MSc in science and technology policy (SPRU, Science and Technology Policy Research, University of Sussex, Brighton, UK), PhD in economics and management of innovations (Sant’Anna School of Advanced Studies, Pisa), is lecturer at Bocconi University and Research Fellow at CESPRI (Research Centre on Processes of Innovation and Internationalisation). Her main research interests include technology diffusion, product and service innovation and industrial dynamics in the ICT sector, with particular reference to the telecommunications industry. Rebecca De Coster, Dr. Rebecca De Coster is a lecturer of innovation in the School of Engineering and Design, Brunel University. She has twelve years experience in the telecoms sector including research and consultancy based on her prior experience in telecommunications planning. She received her BEng (Hons) in electronic and electrical engineering from Birmingham University and her MBA from the University of Kingston, London. She earned her doctoral degree from Brunel University examining innovation strategies of mobile networking firms and the associated enterprise realignment for managing technology and innovation. Walter Distaso is at Tanaka Business School since September 2006. He holds a PhD from the University of York. Previously, he held positions at the University of Exeter and Queen Mary, University of London. He has also been a visiting professor at the IMF. His research interests are in the area of estimation, specification testing and prediction of financial Volatility in continuous time models; analyzing macroeconomic and financial time series using long memory models; identifying the macroeconomic determinants of stock-market volatility; studying the dependence of multivariate financial time series using copulas; evaluating competing trading strategies; analyzing the features and the effects of market microstructure noise; analysis of telecommunications market. His research has been published by leading journals such as Review of Economic Studies, the Journal of Econometrics and the Journal of Business and Economic Statistics. Anastasios A. Economides received the Dipl.Eng. degree in electrical engineering from the Aristotle University of Thessaloniki, in 1984. Holding a Fulbright and a Greek State Fellowship, he received the MSc and the PhD degrees in computer engineering from the University of Southern California, Los Angeles, in 1987 and 1990, respectively. At graduation, he received the Outstanding Academic Achievement Award from the University of Southern California. Currently, he is an associate professor of computer networks at the University of Macedonia, Thessaloniki, Greece. He is the director of CONTA (COmputer Networks and Telematics Applications) Laboratory. His research interests include networking technologies and e-services. He has published over one hundred peer-reviewed papers. He



About the Contributors

has been the plenary speaker in two International Conferences. He has served on the program committees for many International Conferences, and as a reviewer for many International Journals and Conferences. Finally, he has been the principal investigator of several funded projects and participated in many funded projects. Salah Eddine Elayoubi was born in Tripoli, Lebanon, in 1978. He received the engineering diploma in telecommunications and computer science from the Lebanese University in 2000 and the master’s degree in telecommunications and networking from the National Polytechnic Institute at Toulouse, France, in 2001. He completed his PhD degree in computer science and telecommunications in the University of Paris VI in 2004. Since then, he has been working in Orange Labs. His research interests include radio resourse management and performance evaluation of mobile networks. Jose Joaquin Escudero-Garzas received the telecommunication engineer degree from Polytechnic University of Madrid (Spain) in 1997. He worked for different telecommunications companies until 2002. He joined University Carlos III de Madrid in 2002, where he is currently working as an assistant lecturer and working towards the PhD in electrical engineering. He has participated in several national and international research projects. His research areas of interest include resources management for wireless communications, cognitive radios and game theory for wireless networks. Károly Farkas received his PhD degree in computer science in 2007 from ETH Zurich, Switzerland, and his MSc degree in Computer Science in 1998 from the Budapest University of Technology and Economics (BME), Hungary. Currently he is working as an associate professor at University of West Hungary, Sopron, Hungary. His research interests cover the field of communication networks, especially autonomic, self-organized and wireless mobile ad hoc networks. His core research area deals with service provisioning in mobile ad hoc networks. He has published more than 30 scientific papers in different journals, conferences and workshops and he has given a plenty of regular and invited talks. In the years past, he supervised a number of student theses, participated in several research projects, coordinated the preparation of an EU IST research project proposal and acted as reviewer and organizer of numerous scientific conferences. He served in the program committee of the IADAT-tcn conference in 2005 and 2006, and he acted as a technical co-chair of the 3rd WICON (Wireless Internet) conference in 2007. He is a member of IEEE and fellow of the European Multimedia Academy. Claudio Feijóo holds a MSc and PhD in telecommunication engineering from Universidad Politécnica de Madrid, Spain. Currently, he is working at the Institute for Prospective Technological Studies of the JRC of the European Commission where he researches on the future socio-economic impact of emerging information society technologies. He is professor (on leave) in the Universidad Politécnica de Madrid, where he directed the Chair in Telecommunications Regulation and Information Society Public Policies. He was also adviser for the Spanish State Secretary on Telecommunications and Information Society, participating in the design of information society development plans. He lectures regularly in seminars and postgraduate courses and has authored many publications in journals and conferences. Zulima Fernández is professor of strategic management and holds the Chair of Entrepreneuship and Family Firms Management at University Carlos III de Madrid (Spain). She received her PhD from University of Oviedo (Spain). Her research focuses in strategic management, technology management,



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management and privatization of state-owned companies and organization design. Recent papers deal with strategic decisions of SMEs, privatization and first-mover advantages. An example of her empirical research can be found in journals such as Journal of International Business Studies, Journal of International Entrepreneurship, among others Tiago Fioreze is a PhD student at the University of Twente, Enschede, the Netherlands. He is currently investigating the use of self-management in optical networks. He graduated in Computer Science from the Federal University of Rio Grande do Sul (UFRGS) in 2005 (Master of Science) and from the Federal University of Santa Maria (UFSM) in 2003 (Bachelor of Science). His main topic of interest is Network Management, but he also has interest in areas such as Network Security and Fault Tolerance. Roberto Fontana is currently assistant professor in applied economics at the University of Pavia and Research Fellow at CESPRI – Bocconi University. He received his PhD in science and technology policy studies at SPRU – University of Sussex, UK in 2002 and his master of science in science and technology policy studies from SPRU – University of Sussex in 1998. His main interests are in the field of innovation diffusion and standardisation, product innovation, variety and its implications for the dynamics and structural evolution of industries with particular reference to high technology sectors such as computers and communication equipment. Ana Garcia-Armada received the telecommunication engineer degree from the Polytechnic University of Madrid (Spain) in July 1994 and PhD in electrical engineering from the same, February 1998. She is currently working as an associate professor at the University Carlos III de Madrid, Spain where she has occupied several management positions. She has participated in several national and international research projects. She is co-author of four books on wireless communications and signal processing. She has published 22 papers in international journals and more than 40 contributions to international conferences. She has contributed to international organizations such as ITU and ETSI. Richard A. Gershon, PhD, (Ohio University) is professor and co-founder of the Telecommunications & Information Management program at Western Michigan University where he teaches courses in telecommunications management and communication technology & innovation. Dr. Gershon is the author of Telecommunications & Business Strategy (2008 - in press) and The Transnational Media Corporation: Global Messages and Free Market Competition, winner of the 1998 book of the year sponsored by the National Cable Television Center. Dr. Gershon has twice been selected for teaching honors at the national level, including the Steven H. Coltrin Professor of the Year Award (2000) by the International Radio& Television Society (IRTS) and the Barry Sherman Award for Teaching Excellence (2001) by the Management and Economics division of the Association for Education in Journalism and Mass Communication (AEJMC). In 2007, he was the recipient of the Distinguished Teaching Award at Western Michigan University. Dr. Gershon is a founding member of the International Telecommunications Education & Research Association (ITERA) and served as the organization’s first President. David Golightly, holds a doctorate in psychology from the University of Nottingham in ICT-based problem solving. He also has a BSc in psychology (Aberdeen), an MSc in Cognitive Science (Cardiff), and is a chartered psychologist. He has substantial commercial experience in developing and managing human factors research programmes, having lead human factors and systems usability activities in both



About the Contributors

the telecoms and financial services sector. David joined the Human Factors Research Group in 2007, where he continues to manage research programmes exploring human factors in domains such as web, mobile, transport and requirements management. José Luis Gómez-Barroso, holds a PhD and a MSc in economics from Universidad Nacional de Educación a Distancia (UNED). He also holds a MSc in telecommunication engineering from Universidad Politécnica de Madrid as well as another MSc in Law from Universidad Complutense. Dr. Gómez-Barrroso is an associate professor in the Department of Applied Economics and Economic History at Universidad Nacional de Educación a Distancia (UNED). His research interests are focused on telecommunications regulation and public aspects of the development of Information Society. Dr. Gómez-Barroso has participated in different research projects, some of them for the European Commission. He is the co-ordinator of the Spanish Group for the Study of Regulation of Telecommunications (GRETEL). Ricardo Gonçalves is an assistant professor at the Faculty of Economics and Management of the Portuguese Catholic University, in Porto. He has done both consultancy work and academic research on various regulatory and competition aspects of the telecommunications sector. He previously worked in a London based economic consultancy firm. He holds a PhD and a MSc in Economics from the University of York (UK) and graduated in Economics from Instituto Superior de Economia e Gestão (UTL, Portugal). His main areas of expertise are auctions, microeconomics, industrial organisation, and competition policy and regulation. Sotirios K. Goudos was born in Thessaloniki, Greece in 1968. He received the BSc degree in physics in 1991 and the MSc degree in Electronics in 1994 both from the Aristotle University of Thessaloniki. In 2001 he received his PhD degree in physics from the Aristotle University of Thessaloniki and in 2005 the master's in information systems from the University of Macedonia, Greece. Since 1996 he has been working in the Telecommunications Center of the Aristotle University of Thessaloniki, Greece. His research interests include antenna and microwave structures design, electromagnetic compatibility of communication systems, evolutionary computation algorithms and semantic web technologies. Lisandro Zambenedetti Granville is an associate professor at the Institute of Informatics of the Federal University of Rio Grande do Sul (UFRGS), Brazil. He received his MSc and PhD degrees, both in computer science, from UFRGS in 1998 and 2001, respectively. He has served as a TPC member (2003-2008), General Co-Chair (2004), and Steering Committee member (2005-2008) for the Brazilian Symposium on Computer Networks (SBC/LARC SBRC). Currently, he is member of the Brazilian Internet Committee (CBG.br). He has served as a TPC member for IFIP/IEEE IM 2005, NOMS 2006, IM 2007, NOMS 2008 and IFIP/IEEE DSOM 2005, DSOM 2006, DSOM 2007 (TPC Co-Chair), DSOM 2008. His main areas of interest include policy based network management, management using/of Web services, network monitoring and configuration, and P2P-based services and applications. Hyun-Soo Han is an associate professor of information technology management at College of Information and Communications, Hanyang University in Seoul, Korea. He received a BS in industrial engineering from Seoul National University, andMS in management science at Korea Advanced Institute of Science and Technologies (KAIST). He earned PhD in management from University of



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Massachusetts Amherst, USA. Before joined as a faculty member of Hanyang University, he had been with a Korean IT service company as a director of the IS consulting service department. His technical publications appear in various international and domestic journals such as Information & Management, International Journal of Satellite Communications and Networking, International Journal of Technology Management, International Journal of Operations and Quantitative Management, European Journal of Operational Research, Annals of Operations Research, and others. His recent research interests include industry convergence, mobile applications, e-commerce, information systems and telecommunication management. Franz Hartleb received the Diplma degree in computer science from the University of ErlangenNürnberg (Germany) in 1988 and the Doctor of Engineering degree in 1992. From 1993 to 1995 he was affiliated with Siemens AG. Since 1996 he is a senior expert in traffic management and network optimization at the research and development center of Deutsche Telekom (now T-Systems). Currently he is working on IP traffic analysis, traffic modeling, link dimensioning, and QoS guarantee. Gerhard Haßlinger has more than 10 years of experience as a researcher at the computer science department of Darmstadt University of Technology in Germany, as well as in telecommunications industry at T-Systems, where he is currently involved in the design and planning of the broadband access platform of Deutsche Telekom for delivering Internet services with QoS support. His research interests include performance and quality of service aspects in routing, traffic engineering, and peer-to-peer networking. Sunil Hazari is associate professor in the Department of Management, Richards College of Business, University of West Georgia. His teaching and research interests are in the areas of business education, information security, infrastructure design of e-Commerce sites, Web usability, and organizational aspects of e-learning. He has authored several peer-reviewed journal publications in information and instructional technology areas, has presented papers at national conferences, and is editorial board member of several information system journals. Web site: http://www.sunilhazari.com/education Daniel Heil holds a master's in public policy candidate in the School of Public Policy at Pepperdine University. He is specializing in economics and American government. His research interests include telecommunications regulations and the effects of federal programs on poverty and employment. He is currently a research intern with the Hoover Institution. He holds a BA in economics from California State University, Northridge. Trevor Hopper is professor of management accounting at Manchester Business School, and visiting professor at Victoria University of Wellington and Stockholm School of Economics, having previously worked at Wolverhampton and Sheffield Universities, as a cost accountant in industry, and as a visitor at the University of Michigan, Ann Arbor, U.S.A; Queen’s University, Canada; Griffith University, Australia; and Kyushu and Fukuoka Universities, Japan. He has co-edited four books and the British Accounting Review, and is on the editorial boards of several major research journals. He has published in professional journals, books, and research journals including Accounting and Business Research; Accounting, Organizations and Society; the Auditing, Accounting and Accountability Journal; British Accounting Review;



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Critical Perspectives on Accounting; European Accounting Review; Journal of Management Studies; and Management Accounting Research Zoltán Horváth received his MSc degree from the Budapest University of Technology and Economics (BME), where he actually pursues his PhD studies and gives computer networks courses. He has participated in many R&D projects related to planning, testing and building local and metropolitan area networks including WiMAX and community network technologies, as well. He also worked as an advisor for the Hungarian National Communications Authority in applying ETSI regulations, testing devices, EMC measurements and interference examination cooperating with the Hungarian Meteorological Service. Stefan Hüsig has a PhD in business administration and holds the position of assistant professor at the Chair of Innovation and Technology Management at the University of Regensburg, Germany. In addition, he works as a consultant in the area of innovation management, where he has worked with Vodafone R&D, deep innovation, Mannesman Pilotentwicklung, Fraunhofer Technology Development Group and other firms. His research interests are the areas of radical/disruptive innovations, telecommunications, predevelopment, corporate entrepreneurship, and computer-aided innovation. Wesley J. Johnston is the CBIM RoundTable professor of marketing and director of the Center for Business and Industrial Marketing in the Robinson College of Business at the Georgia State University. His research has been published in the Journal of Marketing, the Journal of Consumer Research, the Journal of International Business Studies, the Journal of Business-to-Business Marketing and numerous other publications. He was selected as one of the best researchers in marketing by a recent poll of marketing department chairman in U.S. universities. His number of publications places him in the top three researchers in business-to-business marketing in the world. Mahabaleshwar S. Kakkasageri completed his MTech from Visvesvaraya Technological University Belgaum, Karnataka. He is pursuing his PhD in the area of Vehicular Ad hoc Networks (VANETs). Presently he is serving as an assistant professor in Department of Electronics and Communication Engineering, Basaveshwar Engineering College, Bagalkot, Karnataka. He has published several papers in conferences and journals. Recently he has been listed in Marqui’s Who’s Who in the World. Faouzi Kamoun assistant professor and assistant dean in the College of Information Technology at the University of Dubai, holds a PhD degree in electrical & computer engineering from Concordia University and an MBA from McGill University. Prior to joining the University of Dubai in 2002, he has been a senior technical advisor with Nortel Networks where he made various contributions in the specifications and rollout of many optical networks. Dr. Kamoun current research is focused on the management aspects of communications networks and technologies. Dr. Kamoun was the recipient of Nortel Networks CEO top talent award in 2000 and 2001. He also received the best faculty award from the University of Dubai in 2004 (a university wide competition). He is a member of the Editorial board of the Information Technology Journal and The International Arab Journal of e-Technology (IAJeT). Dimitris N. Kanellopoulos holds a PhD degree in multimedia communications from the Department of Electrical and computer engineering of the University of Patras, Greece. He is a member of



About the Contributors

the Educational Software Development Laboratory (ESDLab) in the Department of Mathematics at the University of Patras. His research interests include multimedia communications, intelligent information systems, knowledge representation and web-based education. He has authored numerous papers in international journals and conferences in these areas. He serves as an editor in ten scientific journals. Georgia M. Kapitsaki is a research associate working towards a PhD at the National Technical University of Athens (NTUA). Her research interests include mobile internet, context-aware services, context modelling and management, software engineering approaches for pervasive computing and service-oriented architectures. She received her Dipl.-Ing from the School of Electrical and Computer Engineering of NTUA in 2005. Antonios D. Kargas received his BS degree in economics and his MSc degree in economics and management of telecommunications at the National and Kapodistrian University of Athens. Currently he is working towards his PhD on the organizational issues of telecommunications industry. His research interests include organizational culture and performance analysis of telecommunications companies as well as economics of telecommunications. Sebastian Kempken has completed his studies in applied computer science at the university of Duisburg-Essen with a thesis on the evaluation of spelling variants by string distance measures. Currently, he is working on his PhD in the project “Verdikom” on the subject of modeling and interval-based analysis of correlated data traffic in service-integrating communication networks. Moon-Koo Kim is a senior researcher in Technology Strategy Research Division of Electronics and Telecommunications Research Institute (ETRI). He received the BA degree in business administration from Yonsei University, Seoul, Korea and the MS degree in management from Information and Communications University (ICU), Daejeon, Korea. He is mainly interested in marketing strategies, forecasting and business modeling, competitiveness, and IT policy. Moon-Soo Kim is an associate professor of School of Industrial & Management Engineering, Hankuk University of Foreign Studies (HUFS) in Korea. He has experienced as a project manager at ETRI (Electronics and Telecommunications Research Institute) for 5 years before joining the university. His research focuses on technology strategy and its various application fields. He has been involved in studies on management of technology, telecommunication service management, and e-business planning & strategy, etc. Dr. Kim has published papers in several international journals such as International Journal of Innovation Management, Scientometrics, Technology Analysis & Strategic Management, Omega, Journal of Scientific & Industrial Research, and Technological Forecasting & Social Change, etc., and also in several domestic journals. He holds a PhD from Seoul National University in Korea. Tobias Kollmann is professor for e-business and e-entrepreneurship at the University of DuisburgEssen, Germany. Prior to his current position, he was a founder of autoscout24, the largest used car electronic trading platform in Europe, and held a professorship for e-business at the University of Kiel, Germany. Professor Kollmann received his doctorate in 1997. Since then, his research interests include e-business, e-commerce, virtual marketplaces and, in particular, business venturing in the Internet economy.

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About the Contributors

Stan Kurkovsky is an associate professor at the Department of Computer Science at Central Connecticut State University. Stan earned his PhD from the Center for Advanced Computer Studies of the University of Louisiana in 1999. The results of his doctoral research have been applied to network planning and industrial simulation. Stan’s research interests are in mobile commerce and pervasive computing, distributed systems and software engineering. He published over 40 papers in refereed proceedings of national and international conferences, scientific journals and books. Stan serves as a reviewer and a member of program committees on a number of national and international conferences. During his academic career, Stan received over a million dollars in funding from private and federal sources. Riku Laanti has MSc (international business) and MBA (finance) degrees from the Helsinki School of Economics, and he is currently finalising his PhD research on the internationalisation of telcos in the University of Adelaide. He also teaches international business and strategy MBA courses in the University of South Australia. In addition to his academic commitments, Mr Laanti offers consulting services in international business and strategy. Riku has a background in the ICT industry where he has worked for more than twelve years, including director positions in Telia Mobile/Telia Finland. Prior to his five-year career in Telia, he was a partner and managing director in one of the leading telecommunications retailers in Helsinki, Finland. Pedro Lázaro received his MSc degree in telecommunication engineering in 1997 from the University of Málaga (Spain). From 1997 to 1999 he worked at the European Space Agency in Darmstadt (Germany). From 1999 to 2001 he worked at the International Telecommunication Union (ITU) in Geneva (Switzerland). Since 2001 he has been with the Communication Engineering Department, University of Málaga. His research interests include satellite and mobile communications, mainly focused on selfregulation of radio networks. Heesang Lee is a professor of systems management engineering at Sungunkwan University in Seoul, Korea. He received a BS and anMS in industrial engineering from Seoul National University in 1983 and 1985, respectively. He got his PhD in Industrial & Systems Engineering from Georgia Institute of Technology, Atlanta, USA in 1991. Before joined as a faculty member of Sunkyunkwan University, he had been with KT and Hankuk University of Foreign Studies as a senior researcher and an associate professor, respectively. His current research interests include IT & telecommunication management, technology innovation, nature inspired modeling, and management of complex systems. His technical publications appear in international and domestic journals including Management Science, European Journal of Operations Research, and Telecommunication Systems. Pierre Lévis received his degree from the Institut National des Telecommunications (INT) Evry France. He has been with France Telecom, R&D Division since 1998. He has worked in the specification, development, and evaluation of IP service offerings. His research interests are QoS, IPv6, network security, and mobile networks. He was an assistant professor at INT from 1990 to 1998, where he was in charge of computer networks courses, and his research interest was on information technology. Chen Li is a post graduate student majored in information management and information system, School of Management and Economics, Beijing University of Posts and Telecommunications. His

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About the Contributors

research interests focus on information integration, SOA and personalized recommendation system. Recently, the integration between BPM and SOA is being researched. Yuanquan Li is a post graduate student majored in management science and engineering, School of Management and Economics, Beijing University of Posts and Telecommunications. His research interests focus on data mining for customer churn prediction, information system adoption and personalized recommendation system. Recently, service modeling for personalized recommendation in telecommunication industry is being researched. Mirko Luca Lobina ([email protected]) is a researcher at the University of Cagliari (Italy) since 2001. His main research topics of interest are in multimedia networking (error recovery and concealment, IP telephony, and QoS in real-time services) and digital property protection mechanisms. He has published several journal articles and refereed conference papers. Dr. Lobina is also a freelance consultant for national and international IT enterprises. Brian Low is a senior lecturer in marketing at the University of Western Sydney. Dr. Low has spent some sixteen years in the automotive, information technology and telecommunication sector, in various marketing and research positions. He has also consulted for a range of American, European and Chinese companies on marketing and internationalizing strategies and regulatory policies in the telecommunication sector in Asia Pacific. His research has been published in the Journal of Business and Industrial Marketing, Industrial Marketing Management and the Journal of Asia – Pacific Business. He is an occasional reviewer for the Journal of Telecommunications Policy. Paolo Lupi works in the economic and competition analysis department of AGCOM, the Italian communication regulator, since 2001. He works both on research-oriented assignments and on-the-field projects. Main areas of expertise include competition analysis and regulatory policy (with a particular focus on fixed networks interconnection and Internet development). Paolo leads the team that is in charge of the analyses, both at retail and wholesale level, of the narrowband and broadband access markets. Paolo is a delegate to the Communication Infrastructures and Services Policy Working Group of the OECD and has participated (also as a chair) in the activities of many Working Groups of the European Regulators Group. Before joining AGCOM Paolo held research positions at the University of Naples (IT) and at the University of York (UK). He holds an MSc and a PhD in Economics from the University of York (UK). Paolo has published in academic and non academic journals on different topics related to the general areas of telecommunications economics and policy. Maria Major, PhD (Manchester), is an assistant professor of management accounting at ISCTE – Business School, Lisbon. Her research interests lie in management accounting change both in private and public organisations. Dr. Major has published in academic journals including Management Accounting Research and The European Accounting Review. She is on the editorial board of Journal of Accounting & Organizational Change and she is additionally active in refereeing articles for a number of leading accounting journals. Currently she is conducting a research project funded by the Portuguese Government on management control in the healthcare sector.

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About the Contributors

Dimitrios G. Makris is an undergraduate student at the University of Peloponnese (UoP). His academic and research interests include mobile communications, network management as well as configuration and software engineering. He is a member of the “Communication Networks and Mobile Systems” laboratory of the University of Peloponnese (cnms.uop.gr) and participates in the “One Laptop Per Child” (OLPC) project. Fabio M. Manenti, associate professor in Economics at the University of Padua (Italy). Ma in Economics at the University of Brescia (Italy), MSc and PhD in Economics at University of York (UK), Dottorato in Economia Politica at the University of Pavia (Italy). Research Interests include industrial organization, networks & Internet economics, software markets, economics of telecommunications, and regulation. Sunilkumar S. Manvi completed his PhD from Indian Institute of Science, Bangalore, India. His areas of research include wireless/wired networks, AI applications in network management and Ecommerce. He has published about 100 papers in journals/conferences. He has coauthored books Communication Protocol Engineering and Computer Concepts and C Programming. He is a reviewer of several international/national journals. He is a member of IEEE, USA, Fellow of IETE, India, Fellow of IE, India and member of ISTE, India. He has been included in Marqui’s Who’s Who in World and International Biographies of Cambridge, London in the year 2006. Carol C. McDonough is a professor of economics at University of Massachusetts Lowell, in Lowell, Massachusetts. A member of the Zoning Board of Appeals in Andover, Mass., she holds an MA and a PhD in economics from Boston College. Dr. McDonough’s primary area of teaching and research is microeconomics, especially applied microeconomics. She has written numerous articles and papers on the wireless telephony industry. Fred McDougall holds a BComm(honours), MComm, and a Dip Ed from the University of Melbourne, a PhD from the University of Adelaide, and is a CPA (Fellow). He is currently the deputy vice-chancellor and vice-president (academic) at the University of Adelaide. He was previously the foundation chair of management, director of the graduate school of management, and executive dean of the faculty of the professions at the University of Adelaide. James M. McKinion is a research electronics engineer with the USDA, Agricultural Research Service, Genetics and Precision Agriculture Research Unit located at Mississippi State, MS. Dr. McKinion has conducted research in cotton crop modeling, controlled-environment plant growth chambers, precision agriculture, and development of wireless networks for farm applications. In a 39 year research career with ARS, he has published over 200 papers in refereed journals, several book chapters and one book. He is a member of the American Society of Agricultural and Biological Engineers and an adjunct professor with the Agricultural and Biological Engineering Department, Mississippi State University. John B. Meisel is a professor in the Department of Economics and Finance at Southern Illinois University Edwardsville. He received his PhD in economics at Boston College. He has published research examining the role of the Internet in transforming various communication and entertainment industries. Other research areas include antitrust, law and economics, and telecommunications.

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About the Contributors

Asunción Mochón received her MSc in economics from Autonoma University of Madrid and her PhD in economics from Universidad Nacional de Educación a Distancia (UNED). Currently, she is an associate professor of economics at Universidad Nacional de Educación a Distancia (UNED) in Madrid. Her research focuses on auctions in several markets, like spectrum licences. Most of her recent work has addressed key questions in multiunit auctions and combinatorial auctions. To this end, evolutionary computation techniques, like genetic algorithms, have been tested in several auctions models. She has published several articles on auctions in major journals and congress. Pierrick Morand has been the project coordinator of the EU IST-MESCAL project. He also leads a research group within France Telecom working to develop and enhance VoIP services for corporate business. He graduated from the Ecole Nationale Supérieure d’Ingénieur de Caen (Institut des Sciences de la Matière et des Rayonnements), a French school of engineers, and received his degree from the University of Caen, France. Frédéric Morlot was born on July 19th 1982 in Lyon (France). He majored in applied mathematics and pure mathematics in École Polytechnique and Telecom Paristech, both French universities. After his graduation, he worked in Orange Labs, the research and development division of France Telecom. At the same time, he is a PhD student in stochastic geometry at the École Normale Supérieure in Paris. His research fields include radio resource management and probabilities. Álvaro Nascimento is the dean of the Faculty of Economics and Management at the Portuguese Catholic University, in Porto, Portugal, and has research and publications in the subjects of regulation of financial markets and telecommunications. He holds a PhD in Finance from Cass Business School (UK) and a MSc in International Trade and Finance from Lancaster University (UK). He was a visiting research fellow at the London Business School in the Regulation Initiative and a consultant to several financial and telecommunication companies on regulatory and competition issues. He was also the lead economist on competition issues for recent M&A operations in Portugal (representing the companies). Ricardo Neisse is a final year PhD candidate at the University of Twente, the Netherlands. He received his MSc degree in 2004 from the Federal University of Rio Grande do Sul, Brazil. His broad research area is management of distributed systems and networks, and the topic of his PhD thesis is security and trust management for context-aware service platforms. He has published several papers and actively contributed as a member of the scientific staff in many international conferences and research projects. Phillip Olla is the endowed Phillips chair of management and professor of MIS at the school of business at Madonna University in Michigan USA, and he is also a visiting research fellow at Brunel University, London, UK. His research interests include knowledge management, mobile telecommunication, and health informatics. In addition to university level teaching, Dr. Phillip Olla is also a chartered engineer and has over 10 years experience as an independent consultant and has worked in the telecommunications, space, financial and healthcare sectors. He was contracted to perform a variety of roles including chief technical architect, program manager, and director. Dr Olla is the associate editor for the Journal of Information Technology Research and the Software / book review editor for the

14

About the Contributors

International Journal of Healthcare Information Systems and Informatics, and is also a member of the editorial advisory & review board for the Journal of Knowledge Management Practice. Dr. Phillip Olla has a PhD in mobile telecommunications from Brunel University in the UK. He is an accredited press member of the British Association of Journalism, chartered IT professional with the British Computing Society and a member of the IEEE society. Claudia Parlanti is currently working at Procter and Gamble Italy (Rome) in the Marketing Department. She received her master's of science in economics and management of international markets and new technologies from Bocconi University, Milan, in 2007 and her degree in economics of international markets and new technologies from Bocconi University, Milan, in 2005. In 2007, she worked for six months at Cisco System Italy (Milan) as a junior analyst. Her main interests include product innovations, technology diffusion and adoption in high tech sectors. Jong-Hyun Park is a senior researcher in technology strategy research Division of Electronics and Telecommunications Research Institute (ETRI). He received the BA degree in economics from Korea University, Seoul, Korea and the MS degree in management from information and communications University (ICU), Daejeon, Korea. He is mainly interested in IT market analysis, marketing strategies and ubiquitous network. Myeong-Cheol Park received the BS degree in the industrial engineering and MS in business administration from Seoul National University, Seoul, Korea. He received his PhD degree in management science from University of Iowa. He worked for ETRI, where he engaged in many research related in IT management and economic issues. He is professor at the school of IT business, Information and Communications University (ICU). He main research interests include IT management and strategies. Harry G. Perros is a professor of computer science, an alumni distinguished graduate professor, and the program coordinator of the Master of Science degree in computer networks at NC State University. He has published extensively in the area of performance modeling of computer and communication systems, and he has organized several national and international conferences. He has also published three print books and an e-book. His current research interests are in the areas of next generation networks, multi-domain routing, resource allocation under QoS, service science management and engineering (SSME), and queuing theory. Samuel Pierre is currently a professor of computer engineering at École Polytechnique de Montréal where he is director of the Mobile Computing and Networking Research Laboratory (LARIM) and NSERC/Ericsson Industrial Research Chair in Next-generation Mobile Networking Systems. Dr. Pierre is the author or co-author of 6 books, 19 book chapters, 17 edited books, as well as more than 350 other technical publications including journal and proceedings papers. James Prieger is an economist at the Pepperdine University School of Public Policy, where he is an associate professor. He specializes in regulatory economics, industrial organization, and applied econometrics. His research includes the impact of regulation on telecommunications innovation, the use of cell phones while driving, the broadband digital divide, the impact of the Americans With Disabilities Act on retail firms, and econometric methodology for non-randomly sampled duration data. Prieger sits

15

About the Contributors

on the editorial board of Applied Economics Quarterly. He received his BA from Yale University and his PhD from the University of California, Berkeley. Jiayin Qi is an associate professor at the School of Economics & Management, Beijing University of Posts and Telecommunications, Beijing, China. Her research interests include customer relationship management and telecommunication operation management. She has published more than 60 papers and 3 books in the two research fields. Sally Rao (hons) PhD CPM is a senior lecturer in marketing at the Business School, University of Adelaide. She is the lecturer in charge of consumer behaviour and e-marketing. Her research interests include relationship marketing, internet marketing, services marketing and technology adoption. She is an active researcher and has published in the Journal of Business and Industrial Marketing, European Journal of Marketing, Qualitative Market research: an International Journal, Australasian Marketing Journal, International Journal of Internet Marketing and Advertising and Journal of Internet Business. She has won the best paper award in an international conference. Salah Ramadan ([email protected]) received hisMS and PhD in systems and computers engineering from Al-Azhar University in 2002 and 2005, respectively. Since 2005, he is a lecturer in systems and computers engineering at Al-Azhar University and an instructor in CISCO academy, Egypt. Currently, he is a research scholar in the Computer Science and Engineering Department, School of Engineering, the Southern Methodist University at Dallas, TX, USA, where he works in post doctoral research. His research interests include mobile computing, cellular networks, and sensor networks. James Salter completed his PhD in the field of optimisation of P2P networks at the Department of Computing, University of Surrey, UK in September 2006. He also holds a BSc in computing and information technology (1st class) from the same University in 2003. He has published numerous research articles in fully refereed journals and international conferences in the fields of peer-to-peer networks and agent-based recommender systems and he has received a number of best paper awards. Yeong-Wha Sawng is a senior researcher of the IT Technology Strategy Research Division at the Electronics and Telecommunications Research Institute (ETRI), Korea. He received an MIM in Management from Whitworth University, USA, and a PhD in information technology management from Hanyang University, Seoul, Korea in 1995 and 2006, respectively. He joined ETRI in 2000, and has been working in the areas of digital convergence, IT policy, mobile application, technology management and business strategy. His research interests also include high-tech marketing, technology management strategy, business model, and consumer behavior. His academic papers were published in several international and Korean journals. Carsten Schröer is a doctoral candidate in the E-Business and E-Entrepreneurship Research Group at the University of Duisburg-Essen, Germany. He received a degree in business administration and international management from the Dresden University of Technology, Germany and holds an MBA from Pfeiffer University at Charlotte, NC, USA. His research is currently focused on business angels, the informal capital market, and e-business.

16

About the Contributors

George Scheets received a BS in general engineering from the United States Military Academy at West Point in 1975, and following five years in the U.S. Army as a Signal Corps officer,MS and PhD degrees in electrical engineering from Kansas State University in 1984 and 1987 respectively.  He is an associate professor at Oklahoma State University. His research interests include telecommunications network analysis and design, teaching in a virtual environment, and secure communications protocols.  He has performed contract research for organizations such as Williams Telecommunications, the U.S. Air Force, Motorola Government Electronics Group, the U.S. Department of Education, and the U.S. Department of Defense. Dong-Hee Shin has been an assistant professor in the School of Information Sciences and Technology at Penn State University since 2004. He earned his PhD andMS in information sciences and telecommunications from Syracuse University. He has been researching on telecommunications management and policy and he had various consultancy experiences in the field of telecommunications and information industry. His current project looks at the consequences of governmental policy and regulations on telecommunications and information infrastructure as well as the applications and implications of these services. He is also interested in evaluating the process and impact of large technological projects and policy by using qualitative and quantitative case study methods. His publications have appeared in several international journals such as Information Research, Technological Forecasting & Social Change, INFO, and Telematics and Informatics. Yajing Si is a lecture professor at the school of Logistics, Beijing Wuzi University, Beijing, China. Her research interests include the customer relationship management and telecommunication operation management. She is also a PhD candidate at Beijing University of Posts and Telecommunications. Darko Skorin-Kapov is a professor of information technology and operations management at the School of Business, Adelphi University, New York. He received his PhD in management science from the University of British Columbia, Vancouver, Canada, and MSc in information science and BSc in mathematics from Zagreb University, Croatia. He authored numerous research papers in management science and related areas. His research interests are focusing on optimization and cost allocation in communication networks. Dr. Skorin-Kapov is a recipient of a number of awards and grants, including Bender Award, Fulbright Award, and National Science Foundation Grants. Jadranka Skorin-Kapov is a professor of operations management at the College of Business, Stony Brook University. She received a PhD in operations research from the University of British Columbia in Canada, a PhD and MA degrees in Philosophy from Stony Brook University in USA, and a MSc and BSc degrees in mathematics from the University of Zagreb in Croatia. Her research includes applications of discrete optimization to telecommunications, network design, manufacturing design, scheduling, and location and layout. She authored many research papers and is a recipient of a number of grants, including six National Science Foundation grants. Marc St-Hilaire received the computer engineering degree from Concordia University in 2002 and the master and PhD degrees in computer engineering respectively in 2003 and 2006 from the École Polytechnique de Montréal. Dr. St-Hilaire is currently an assistant professor in the Department of Systems and computer engineering at Carleton University. His research interests include telecommunication network planning, mathematical modeling and meta-heuristics. 17

About the Contributors

Christoph Stöckmann is a doctoral candidate in the E-Business and E-Entrepreneurship Research Group at the University of Duisburg-Essen, Germany. He received a degree in business informatics from the University of Duisburg-Essen, Germany. His research is currently focused on strategic management, corporate entrepreneurship, entrepreneurial orientation, ambidextrous innovation, and e-business. Timothy S. Sullivan is an instructor in the Department of Economic and Finance at Southern Illinois University Edwardsville. He received his PhD in economics at the University of Maryland. He has published research examining the role of Internet portals and the Internet’s effect on the music and motion picture industries. Other research areas include local economic development and statistical methods. Csaba A. Szabó received his PhD degree from the Budapest University of Technology and Economics (BME) and a Doctor of Technical Sciences title from the Hungarian Academy of Sciences. He is a Professor at the Dept. of Telecommunications of BME. He has been also with Create-Net, an international research center, based in Trento, Italy, as a Senior Advisor since 2004. His 30+ years of experience in academia, R&D and telecommunication business includes metropolitan area networks, integrated services wireless networks, video conferencing and media streaming, broadband optical and wireless networks, community network technologies and applications. Dr. Szabó has been a member of editorial boards of several journals including Computer Networks, and is the editor-in-chief of the Hungarian journal Telecommunications. He has been general chair and steering committee chair of several international conferences, including Multimedia Services Access Networks (MSAN), the 1st Int’l IEEE/Create-Net Workshop on Telemedicine over Broadband (BroadMed), and the series of IEEE/Create-Net Conference on Testbeds and Research Infrastructures (Tridentcom). Dr. Szabó is a co-editor and co-author of a recent Wiley book titled Broadband Services: Business Models and Technologies for Community Networks. He is a senior member of IEEE. Jing Tan is a post graduate student in the School of Economics and Management of Beijing University of Posts and Telecommunications (BUPT), majoring in the Management Science and Engineering. She graduated from BUPT and received her bachelor’s degree of business administration in July, 2007. Her research interests focus on the Customer Relationship Management (CRM), especially in the telecommunication industry. Katalin Tarnay is professor emeritus at the University of Pannonia (Veszprém, Hungary). She received MSc degree from the Technical University of Budapest in 1956, PhD degree from the Hungarian Academy of Sciences in 1974. She developed software tools and methods for protocol engineering first in the Central Research Institute for Physics, and later in NOKIA Hungary. At the same time she was appointed full professor of the University of Pannonia and honorary professor of the Technical University of Budapest. She was author of the book Protocol Specification and Testing (Plenum Press, New York, 1991.) Indrit Troshani PhD, MSc (computer-based InfoSys), GradCertEd (TertTeach), BBA (hons), MACS, teaches Internet commerce, electronic commerce, and information systems at both undergraduate and postgraduate levels at the Business School, University of Adelaide. His research interests include adoption and diffusion of network innovations (e.g. XBRL) and mobile services (e.g. 3G). Indrit’s work has appeared in European Journal of Innovation Management, Electronic Markets, International Journal

18

About the Contributors

of E-Business Research, Journal of Theoretical and Applied Electronic Commerce Research and others. Indrit is a member of Australian Computer Society. Nikolaos D. Tselikas is a research associate in the School of Electrical and Computer Engineering of National Technical University of Athens (NTUA) and a visiting lecturer in University of Peloponnese (UoP). He is a reviewer in several IEEE and Elsevier journals and his research interests include service-oriented architectures, service creation and control, context-aware services, location based services, distributed systems as well as middleware and software engineering. He received both his Dipl.-Ing. degree and his PhD from the School of Electrical and Computer Engineering of NTUA in 1999 and 2004, respectively. Belén Usero is an assistant professor of Strategic Management at University Carlos III de Madrid (Spain). She holds a PhD in economy and a Licentiate degree in Business Administration (University Carlos III de Madrid). Previously, she has taught strategic management at University of Salamanca. Her main research interests include first- mover advantages in mobile telecommunications industry, corporate strategy of SME, non-market strategy and business models. She has published her research in national and international journals such as Service Business — an international journal Dimitris Varoutas holds a physics degree and MSc and PhD diplomas in communications and technoeconomics from the University of Athens. Since 2005, he is a lecturer on telecommunications technoeconomics in the Department of Informatics and Telecommunications at the same university. He actively participates in national and EU-funded R&D technoeconomic activities for telecommunications, networks and services such the ICT-OMEGA and the CELTIC/CINEMA projects, as well as the Conferences on Telecommunications TechnoEconomics. His research interests include optical and wireless communications systems, technoeconomic evaluation of network architectures and services and demand and price modeling. He has published more than 40 publications in refereed journals and conferences in these topics and he is a member of several IEEE societies, serving as a reviewer. Iakovos S. Venieris is a professor in the School of Electrical and Computer Engineering of NTUA. His research interests are in the fields of broadband communications, Internet, mobile networks, intelligent networks, internetworking, signaling, service creation and control, distributed processing, agents technology, and performance evaluation. He received his Dipl.-Ing. degree from the University of Patras in 1988, and his PhD degree from NTUA in 1990, all in electrical and computer engineering. He is a reviewer for several IEEE, ACM, Elsevier, and John Wiley journals, associate editor for the IEEE Communications Letters, member of the editorial staff of Computer Communications (Elsevier), and has been guest editor in the IEEE Communications Magazine. Prof. Venieris is the co-editor of two international books on Intelligent Broadband Networks (Wiley 1998) and Object oriented Software Technologies in Telecommunications (Wiley 2000). Hannu Verkasalo acts as a project manager of the national research project MoMI (Modeling the Mobile Internet Usage and Business) at the Helsinki University of Technology in Finland. Hannu Verkasalo has actively published on the evolution of the mobile services market. He is currently finishing his doctoral dissertation on the emergence of the mobile Internet and associated empirical research methods. Verkasalo has particularly focused on the empirical modeling of mobile services, utilizing

19

About the Contributors

the recently developed handset-based research method. In addition to research work and consulting in the mobile industry, Verkasalo gives lectures on network economics, operator business and telecommunication regulation. Ricardo Lemos Vianna received his BSc and MSc degrees, both in computer science, from the Federal University of Rio Grande do Sul (UFRGS) in 2003 and 2007, respectively. His main topic of interest is the use of Web services technologies, especially service composition using WSBPEL, applied to computer network management. Barney Warf is professor of geography at the University of Kansas. His research and teaching interests lie within the broad domain of human geography, particularly economic and political issues. His work straddles contemporary political economy and social theory on the one hand and traditional quantitative, empirical approaches on the other. His work focuses primarily on the dynamics of the service economy, including the telecommunications industry, New York as a global city, electronic financial markets, offshore banking, international legal and engineering services, the geographies of cyberspace, the regional impacts of military spending, political geography, and time-space compression. He is also interested in different perspectives on the philosophy of space and time. He has authored, co-authored or co-edited seven books, 25 book chapters, and 85 journal articles, and won teaching and research awards. Ran Wei (PhD, Indiana University, 1995) is an associate professor in School of Journalism & Mass Communications at the University of South Carolina, USA. His research interest focuses on the adoption, use and impact of new media technology in national, organizational, and individual contexts. He is a renowned scholar in the emerging field of mobile communication. His publications include 40 refereed journal articles and book chapters, and one co-authored book. James G. Williams received his PhD from the University of Pittsburgh in Information and computer science in 1972. After teaching at the University of South Caroline from 1972 to 1974 he returned to the University of Pittsburgh’s Department of Information Science as an assistant professor in 1974 and was promoted to full professor in 1984. He served as department chairman from 1985 to 1993. He retired from the University of Pittsburgh as a Professor Emeritus to become CIO of Broadstreet Communications, Inc. and later become president of Automated Systems Research and Development, Inc., a position he currently holds. During his academic career he published nearly 100 journal and proceedings articles, co-authored 2 encyclopedias with Allen Kent, and co-authored 5 books and received millions of dollars in research grants. Kaiqi Xiong is currently on the faculty of the Department of Computer Science at Texas A&M University, Commerce, Texas, United States. He has received the PhD degree in computer science and theMS degree in computer engineering from the North Carolina State University, and the PhD degree in mathematics from the Claremont Graduate University. He has served as a TPC member for a variety of international conferences, such as IEEE ICC’07, IEEE Globecom’08, CSA’08, and IEEE ICC’09. His current research interests are in the areas of computer and network security, distributed service computing, performance evaluation, and next generation networks

20

About the Contributors

Zaharias D. Zaharis received the BSc degree in physics in 1987, the MSc degree in electronics in 1994 and the PhD degree in physics in 2000, all from the Aristotle University of Thessaloniki, Greece. Since 1993 he has been working as a research assistant in the Radiocommunications Laboratory at the Department of Physics, Aristotle University of Thessaloniki, Greece. Since 2002 he also has been working in the Telecommunications Center of the Aristotle University of Thessaloniki, Greece. His research interests include design and optimization of antenna arrays, design and optimization of microwave circuits and systems, mobile communications systems, RF measurements, wave propagation, electromagnetic scattering and computational electromagnetics. Mohamed Zaki is the professor of software engineering, Computer and System Engineering Department, Faculty of Engineering, Al-Azhar University at Cairo. He received his BSc and MSc degrees in electrical engineering from Cairo University in 1968 and 1973 respectively. He received his Ph. D. degrees in computer engineering from Warsaw Technical University, Poland in 1977. His fields of interest include artificial intelligence, soft computing, and distributed systems. Yangming Zhang received his bachelor’s degree of management information systems and Master degree of management engineering from Beijing University of Posts and Telecommunications (BUPT), China, in 2000 and 2003, respectively. He is currently pursuing his PhD degree of management science in BUPT. His research interests include customer relationship management (CRM) and business intelligence. Yingying Zhang received both her bachelor’s degree and master’s degree of information management and information systems from Beijing University of Posts and Telecommunications (BUPT), China, in 2004 and 2008 respectively. During her undergraduate period, she also minored in telecommunication engineering. Her research interests include customer satisfaction measurement, customer relationship management and customer behavior analysis. Zizhong Zhao (PhD, Communication University of China, 2004) is associate professor and director of The Center for New Media Studies at the Communication University of China, Beijing, China. His research interests include strategies of radio, film and TV industries in China, media convergence, and developments of a Cultural Media Recreation Park in Beijing. He is a consultant to China’s telecommunications policymakers and several Chinese cable system operators. He has published four books.

21



Index

Symbols 3G 39,  45,  76,  88,  109,  118,  170,  181,  191,  251,  255,  256,  263,  264,  325,  352,  353,  354,  357,  361,  365,  376,  437,  445,  477,  499,  513,  515,  519,  520,  650,  651,  709,  722,  742,  756,  757,  815,  963,  974,  980,  985,  989,  995,  996,  1000,  1003,  1004,  1018,  1019,  1023,  1029,  1034,  1041

A access network 2,  13,  48,  49,  50,  51,  53,  63,  225,  236,  238,  256,  443,  444, 445,  519,  521,  522,  638,  640,  822,  825,  944,  950,  951,  983,  1003 access network planning 521 acquisitions 83,  314,  321,  985 activity-based costing (ABC) 282 actualization algorithm 400,  401,  407,  410,  411 agent 197,  489,  490,  494,  495,  505,  506,  507,  509,  606,  611,  612,  726,  727,  728,  729,  730,  731,  732,  733,  734,  772,  820,  822,  824,  825,  826,  827,  828,  829,  830,  831,  832,  833,  834,  835,  870,  915,  938,  971,  972,  988,  996,  1008,  1010 allocation bases 283,  293 amplifier 949,  953,  955,  977,  1034 analytic hierarchy process 414,  415,  430,  431,  981 anomaly detection technique 761 anti-competitive behavior 149 argumentative agents 829

artificial intelligence 308,  368,  377,  399,  755,  756,  757,  801,  802,  834,  960,  966,  982,  984,  996,  1001,  1003,  1004,  1009,  1013,  1023,  1024,  1029,  1030,  1035 asynchronous transfer mode 617,  702,  775,  776,  777,  955 auction 39,  40,  79,  80,  82,  83,  86,  87,  824,   825,  826,  827,  835,  994 audit 265,  268,  269,  270,  271,  274,  275,  280,  541 automated meter reading (AMR) 635,  651,  1028 automatic call distribution (ACD) 460 autonomy 289,  824,  894,  1011

B backup 218,  533,  619,  620,  844,  863,  878,   950 bargaining power 150,  152,  153 bayesian networks (BN) 746 bell operating companies (BOCs) 17 bitstream access 13 black hole 609 bootstrap server 892 bottleneck 5,  49,  50,  53,  59,  60,  210,  335,   336,  596,  784,  840,  857,  873,  875,  910,  911 broadband 137–170,  257,  430–459,  571,  572,  578,  583–597,  616,  634,  650,  723,  779,  786,  848,  852,  856, 865,  925,  945–988,  993,  1006–1040 broadband Internet access 15,  17,  20,  23,  127,  130,  132,  133,  134,  136,  459,  846,  1020

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Index

broadband service providers 126,  127,  131,  133,  134,  135,  136,  137 brokerage services 828 buffer 693,  762 build out systems 68 business case 434,  439,  446,  587,  1040 business model 101,  116,  236,  237,  238,  239,  240,  246,  648,  651,  968 business planning 433,  446 business process innovation 472 buyer agent 826,  827,  831

C cable company 130,  246 cable networking 466,  472 cable TV networks 11,  542,  543,  544,  545,  546,  547,  548,  549,  550,  551,  552,  553,  554,  555,  556 cache 880,  925,  1021 call forwarding service 713,  715,  717 capital intensity 179,  181,  187 chief knowledge officer 274 China 66,  103,  117,  122,  146,  147,  148,  150,  155,  216–295,  314,  364,  369,  376,  379,  398,  542,  574,  582,  637,  772,  773,  785,  958,  971,  972,  993,  997,  1006,  1013,  1014,  1025,  1028,  1036,  1038 Chord 880,  882,  885,  886,  887,  888,  889,  890,  891,  892,  893,  894,  1032 churn prediction model 381 co-regulation 99,  104 code-division multiple access (CDMA) 578,  584 codec 697 cognitive radio 788,  789,  790,  791,  793,  797,  799,  801,  802,  803,  961,  997,  1004,  1029 competition 16,  18,  19,  21,  24,  25,  27,  28,  30,  31,  35,  38,  39,  42,  43,  52,  54,  56,  57,  58,  59,  60,  61,  62,  63,  66,  72,  73,  74,  171,  172,  175,  176,  180,  182,  184,  186,  189,  191,  194,  195,  689,  691,  924,  969,  978,  980,  986,  991,  993,  996,  998, 1001,  1005,  1038,  1041



competitive local exchange carrier (CLEC) 30 content delivery networks (CDNs) 868 context-awareness 477,  478 context analysis 660,  670 contractual relationships 95,  104 convergence 26,  27,  108,  121,  125,  126,  127,  129,  130,  131,  134,  137,  175,  186,  191,  223,  223,  224,  225,  227,  229,  231,  232,  234,  237,  397,  449,  709,  785,  831,  872,  878,  966,  970,  973,  1009,  1017,  1040 conversational services 855 core network planning 521 cost accounting 281,  282,  283,  290,  291,  292,  293,  1028 cost reduction 626 critical mass 328,  557,  558,  559,  562,  564,  566,  567,  569 critical success factors 280,  1040 customer churn 363,  383,  399 customer demand 364,  368,  371,  372,  374,   375 customer Detainment 379,  381,  391,  395,  399 customer detainment value 395 customer loyalty 377,  1031 customer relationship decline phase 399 customer retention 363 customer satisfaction 351,  363,  402 customer value 236,  237,  238,  239,  240,  241,  366,  367,  368,  377 customer value hierarchy 364,  366,  367,  369,   370,  375,  377

D data model 496,  615,  616,  620,  621,  630 dedicated short range communications 600,  612,  976 denial of service 533,  592,  762,  934 denial of service attack 761,  765,  933 deregulation 171,  190,  211,  221,  316,  547,  628,  1014,  1021 detainment response hierarchy analysis 389,  399 diagnosis 538,  545,  742,  743,  744,  745,  746,  747,  748,  749,  750,  751,  752, 

Index

753,  754,  755,  756,  757,  758,  962,  963,  969,  999,  1013,  1017 diffusion 11,  16,  27,  29,  31,  88,  90,  92,  94,  101,  103,  104,  112,  120,  146,  158,  170,  418,  439,  447,  448,  449,  455,  457,  458,  459,  557,  561,  563,  564,  565,  566,  571,  572,  573,  574,  576,  584,  586,  587,  689,  957,  960,  963,  968,  972,  974,  975,  989,  1033,  1035,  1037,  1040,  1042 digital cable TV networks 542,  545,  546,  547,  548,  549,  550,  551,  552,  553,  554,  555,  556 digital divide 156,  157,  652,  1024 digital subscriber line (DSL) 17,  129,  546 digitization 211,  543,  545,  547 dimensioning 412,  852,  860,  965 disruptive potential 113 disruptive technology 109,  123,  894,  1011,  1017 distance learning 616,  622,  623,  624,  625,  631,  783,  995 distributed hash table 894 domain name system (DNS) 541 Dutch auction 825,  827 dynamic efficiency 14 dynamic host configuration protocol (DHCP) 527 dynamic programming 400,  401,  412,  413,  950 dynamic spectrum access (DSA) 36,  790,  797

E e-community 558,  559,  560,  569 e-marketplace 558,  559,  560,  569 earnings sharing regulation 21 eBay 129,  139,  462,  477,  483,  568,  966,  978,  1007 efficiency 1,  14,  28,  62,  308,  657,  763,  864,  872,  884,  907,  981,  986,  990 efficient frontier 895,  896,  903,  904,  905,  906,  907,  908 electronic commerce 474 electronic data interchange (EDI) 101,  210,  975 English auction 826

enterprise attributive analysis 399 enterprise resource planning 465,  468,  472 entrants 123,  583 ex ante regulation 43,  53,  54,  55,  61,  980

F Federal Communications Commission (FCC) 17,  40,  66,  132,  546 fiber optics 208,  209,  210,  211,  212,  213,   214,  216,  217,  218,  219,  220,  543,   544,  545,  779,  943,  970,  975,  991,  1007 financial tangible factors (FTF) 417 firewalls 529,  592,  594,  596,  608,  629,  725,  738 first-mover advantages 205 first generation cellular networks 516 first mover advantages 204,  984 fitness function 919 forbearance 60 forecasting 122,  123,  441,  442,  444,  445,  446,  459,  631,  785,  970,  971,  974,  975,  991,  1009,  1027 fourth generation cellular networks 522 full local loop unbundling 14

G game theory 798,  813,  809,  810,  811,  816,   817,  804,  809,  804,  810,  811,  813,  816,  817,  818,  831,  835,  965,  1007,   1016 general packet radio service (GPRS) 476 genetic algorithm 524,  909,  954,  991,  1029 gigabit ethernet 775,  778,  785,  971 global cities 211,  214,  220,  988 globalisation 189,  191,  989 global planning problem 519,  522 government policy 98,  231,  235,  245 government regulation 26,  65,  66,  196,  231 gray hole 609

H hacking 602 high-speed networks 775,  786,  1007,  1019 home network 222,  225,  233,  234,  235,  246,  968,  1000,  1001,  1011,  1013



Index

horizontal competition 128,  135 horizontal merger 75 HSDPA 229,  352,  353,  357,  361,  362,  363,  400,  401,  410,  522,  572,  639,  845,  1000 human resources management 301 Hurst parameter 760,  763,  765,  769,  770,  771,  772

I i-mode 476 ICT industry 191 image analysis 836,  840,  841,  842 incentive regulation 17,  20,  21,  22,  26,  27,  28,  29,  31,  171,  958,  988,  1002,  1025 incumbents 123,  200 indirect costs 288 industrial networks 263 industry structure 169 industry value chain 437 inequity 147 innovation application 439 intangible factors 418 integrated network management 740,  939,  983,  1004,  1013,  1032 intellectual property protection 95,  104 interactive services 855 interconnection 141,  142,  146,  156,  157,  493,  494,  500,  503,  507,  513,  583,  787,  994,  995,  1010 interference temperature 792,  797,  798,  799,   800,  802,  963,  982,  1038 internationalisation process 174,  177,  179,  180,  181,  183,  187,  192 International Telecommunication Union Telecommunication Standardization Sector (ITU-T) 490,  494,  505 Internet Balkanization 157 Internet engineering task force (IETF) 494,  499,  672,  708,  722,  723,  725,  739,  740,  880,  969,  989,  990,  997,  1009,  1020,  1024 Internet traffic statistics 853 investment modes 420,  421,  423,  426,  427,   429



IP address management 526,  527,  541 IP telephony 631,  689,  690,  691,  692,  693,  698,  961,  978 IPv6 150,  225,  511,  512,  530,  534,  536,  537,  538,  539,  540,  541,  591,  593,  870,  879,  969,  976,  977,  996,  999,  1024,  1037,  1039

J JAIN 703,  704,  706,  708,  709,  711,  714,  715,  716,  717,  718,  719,  720,  721,  722,  723,  964,  996,  997,  1022,  1033,  1035 JAIN API 704,  718,  719,  720 jitter 699,  701,  787,  998 joint ventures 321,  323,  977 just-in-time manufacturing 468,  473

K key performance indicators (KPI) 701 KM processes 267,  268,  269,  270,  271,  277 KM strategies 265,  269,  270,  271,  273,  278,  971 knowledge acquisition (KA) 377 knowledge development 97,  189,  997 knowledge management systems 278,  971

L ladder of investment 1,  6,  13,  14,  969 layer management 494,  495 least-squares estimations 400 legitimacy 248,  249,  254,  255,  256,  257,  258,  259,  260,  263 licenses 37,  39,  40,  41,  42,  46,  47,  66,  67,  68,  69,  70,  72,  73,  76,  77,  78,  79,  80,  83,  86,  91,  96,  104,  196,  201,  582 load balancing 856,  863 local area network (LAN) 591,  787,  837,  843,  847 local loop unbundling (LLU) 14

M Malaysia 159,  168,  265,  266,  267,  269,  271,  279,  280,  344,  998,  1005,  1032,   1040

Index

managed object 489,  490,  505,  507 management information base (MIB) 489,  490,  492,  497,  500,  505 Marconi 281,  282,  285,  286,  287,  288,  289,   290,  291,  293,  294 market access 96,  104 market structure 170,  978 medium access control (MAC) 805 mergers 72,  83,  170,  220,  314,  321,  323,  534,  554,  595,  970,  981,  985,  1038 mesh 36,  445,  519,  572,  577,  636,  638,  639,  640,  641,  642,  644,  645,  646,  650,  652,  686,  805,  812,  817,  873,  874,  875,  902,  903,  904,  905,  906,  907,  952,  953,  954,  970,  988,  989,  999,  1014 message exchange 497,  498,  503,  876 metro networks 944 microcontroller 842,  847 middleware 483,  484,  720,  965,  998 mixed integer linear programming 897 mobile data network 400 mobile Internet 342,  343,  344,  485,  495,  509,  573,  985,  1025,  1036 mobile service 102,  344,  1000,  1036,  1037 mobile service operators (MNOs) 118 mobile Services 81,  85,  103,  104,  171,  327,   342,  343,  344,  586,  669,  723,  982,  991,  1015,  1017,  1018,  1022,  1029,  1031,  1035,  1036,  1037 mobile user 342,  438,  439,  441,  444,  478,  518,  521,  525,  573,  608,  910,  911,  912,  913,  988 mobile virtual network operator 158,  172 mobile WiMax 575,  576,  577,  578,  579,  580,  581,  584,  585 movement behavior 912,  913,  919 multimedia applications 782 multimedia services 344,  722,  1017,  1036 multi protocol label switch 945 mutual information 385 MySpace 482

N Nash equilibrium 807,  808,  814,  815,  831,  832

Net economy 557,  558,  559,  564,  566,  567,  569 network carrier 450,  895,  901,  902 network dimensions 912 network industries 178,  183,  189,  191,  193,   983,  1029 network layers model 125,  127,  128,  132,  133,  136,  137 network management 489,  492,  493,  496,  502,  503,  505,  508,  509,  512,  513,  538,  541,  554,  616,  617,  725,  739,  740,  741,  745,  780,  939,  965,  969,  983,  990,  1004,  1013,  1020,  1021,  1026,  1029,  1032,  1042 network planning 294,  521,  524,  525,  615,  625,  756,  852,  908,  997,  1011,  1025 network positions 263 network resource 394,  396,  503,  777,  825 network security 772,  959 neutrality 45,  139,  140,  591,  981,  984,  1018,  1029,  1042 neutral network 371,  373,  376 next generation networks 33,  48,  62,  709,  723,  803,  1008 next generation networks (xGN) 1,  522,  788,  798,  864,  869,  871 nodal distribution 897,  902 non-market actions 205 non-market environment 205 non line of sight (NLO) 639

O open system 502 optical transport network 775,  781 optimal design 895,  896,  924 organizational culture 298,  304,  308,  309,  316,  323,  974,  1037 organizational iceberg 297 organizational reputation 264 OSA/Parlay 703,  704,  706,  707,  708,  709,   711,  712,  713,  714,  715,  716,  718,  719,  720,  721,  722,  723,  980,  1011,   1035 OSA/Parlay APIs 703,  704,  706,  707,  708,  709,  712,  719,  722,  1011 overlay networks 325,  868



Index

P packet 229,  353,  363,  400,  412,  476,  519,  522,  591,  593,  609,  639,  687,  691,  699,  687,  722,  775,  815,  845,  880,  870,  945,  959,  977,  979,  995,  1007,  1012,  1023,  700,  699 paging 917,  925,  1021 passive splitter 951 peer-to-peer (P2P) networking 868,  871 peering arrangement 141 personalized recommendation 366,  375,  376 pervasive computing 475,  476 physical (PHY) layer 805 platform 11,  12,  51,  80,  91,  126,  127,  129,   134,  136,  137,  167,  224,  229,  230,  238,  240,  244,  546,  547,  548,  550,  553,  557,  558,  559,  560,  561,  562,  563,  564,  565,  566,  567,  569,  612,  649,824,  825,  853,  856,  863,  872,  876,  879,  931,  940,  1008,  1028 Playout 689,  694,  699,  961,  984 Portuguese telecommunications 281,  282,  285,  286,  292,  293,  992,  1007 precision agriculture 836,  848,  849,  1010 precision guidance 837,  838,  839,  847 preliminary success factors 265,  268,  269,  270,  271,  277 price cap regulation 19,  21,  24,  27,  968 privacy 94,  100,  105,  479,  480,  494,  589,  594,  595,  596,  599,  601,  603,  605,  606,  607,  608,  610,  612,  794,  997,  1002 private branch exchange (PBX) 460 proactivity 824 process innovation 14,  19,  20,  21,  22,  26,  31,  461,  462,  463,  464,  466,  470,  472,  473 product innovation 21,  30,  122,  976,  987 production frontier 895,  896 protection of minors 100 protocol 26,  127,  129,  130,  142,  443,  460,  489, 505,  506,  507,  508,  509,  510,  511,  534,  536,  537,  539,  540,  541,  545,  572,  584,  700,  701,  702, 



705,  708,  709,  717,  720,  723,  736,  737,  738,  781,  787,  795,  811,  823,  824,  825,  827,  829,  830,  831,  835,  854,  855,  856,  866,  867,  869,  870,  871,  872,  876,  877,  879,  880,  881,  882,  885,  894,  944, 1032 protocol evaluation 741 protocol gateway 741 protocol independent multicast (PIM) 460 prototyping 662,  670 provider backbone transport 775,  780 psychic distance 177,  180,  181 public-private partnership (PPP) 647 public switched telephone network (PSTN) 460,  517,  588,  701,  762

Q quality of service (QoS) 496,  523,  591,  672,  702,  787,  865,  939,  942

R radio access network (RAN) 742,  758 radio subsystem planning 517,  520 rate freezes 19,  24 rate of return regulation (RORR) 19 real options 412,  415,  416,  420,  422,  430,  431,  960,  966,  1012,  1034 reconfigurability 789 reengineering 464,  471,  473,  989 regionalisation 187,  190,  1020 regulatory delay 20,  22,  23,  26,  29,  1020 regulatory regime 61,  105,  969 reliability problem 519 remote sensing 840,  848,  849,  1027,  1040 resilient packet ring 775 resource-based view 241 resource complementarity 242,  246,  990 resource optimization 927 resources access 97 response time 939 return on investment 434,  435,  540,  634,  1021 ROC curve 384,  385 ROME 882,  885,  886,  887,  888,  889,  890,  891,  892,  893

Index

S scarce resource 34,  790,  809 scenarios 342,  426,  427,  442,  649,  662,  666,  874,  998 secondary spectrum market 38 second generation cellular networks 516 self-similarity 764 seller agent 826,  827,  831 service availability 514,  532,  672,  928,  930,   935,  936,  937 service level agreement 927 service neutrality 37,  42 service overlay 896,  897,  901,  902,  903 service overlay with growth problem (SOGP) 897 service provision 619,  620,  621,  705,  710 shared access 14 signaling traffic 879,  910,  994 signature based detection system 762 simple object access protocol (SOAP) 707,  726,  727,  741 SingTel 106,  172,  180,  181,  182,  183,  193,  1040 small and open economies (SMOPECs) 173,  174 Sonera 180,  181,  182,  206,  318 spectrum sensing 790,  791,  792,  793,  795,  796,  798,  799,  800,  801,  802,  968,  985,  1032 spoofing 538,  605,  608,  613,  1042 static efficiency 14 statistical multiplexing 777,  859,  863,  865 strategic alliances 321,  985 streaming services 855 subsidies 97,  357,  360 supplier agent 828 supply chain 468,  469,  473 sustaining technology 119 switching barrier 363 SWOT analysis 615,  617,  628,  630 SYN-Flood attack 765

T tampering 605 Telcos 186,  192

telecommunication risks 419 Telecommunications Act of 1996 18,  70,  82,  84,  132,  133,  140,  554,  979,  1009 telecom policy 251 Telia 180,  181,  182,  206,  318,  321,  341,  962,  981 Telstra 106,  155,  180,  181,  183 tender 40,  660 throughput 753,  892,  928,  940 toll fraud 620,  630 total cost of ownership (TCO) 529,  537 trading process 827 traffic engineering 687,  864,  865,  990,  1004 transport-multi-protocol label switching 781 triple play 49,  50,  51,  130 troubleshooting (TS) 743 trustworthiness 481 TV whitespace 846,  847,  848 two-tiered Internet 126,  137,  138

U ubiquity 821 unbundled network elements (UNEs) 18,  20 unbundling 13,  14,  62,  122,  986,  990,  991,  1019 uncertainty 412,  430,  573,  756,  757,  966,  978,  1025,  1030 unlicensed spectrum 81,  583,  790,  797,  798,   800,  839,  846,  973 upgrading investment 400,  411,  412,  1012 user-centred design 670 user information table 912

V value chain 463 value network 110,  111,  116,  117,  119,  123,   173,  174,  175,  180,  182,  185,  186,  187,  192 value networks 102,  173,  175,  190,  192,  1000,  1004 virtual onion 296 virtual private networks (VPN) 867 Voice over Internet Protocol (VoIP) 109,  111,  127,  132,  460,  588



Index

W

Y

wavelength assignment problem 946,  951 wavelength conversion 948 wavelength division multiplexing (WDM) 942,  946 Web 2.0 474,  482,  557,  558,  559,  560,  561,  562,  563,  564,  565,  566,  567,  568,  569,  570,  1015 Weiser, Mark 474,  475,  477,  483 wireless access in vehicular environments (WAVE) 607 wireless local area network (WLAN) 117,  639 worm-hole 609

YouTube 481,  482



Z ZigBee 605 zoning ordinances 70